U.S. patent number 11,254,611 [Application Number 16/465,448] was granted by the patent office on 2022-02-22 for cement production.
The grantee listed for this patent is GCP Applied Technologies Inc.. Invention is credited to Elise Berodier, Elizabeth Burns, Josephine H. Cheung, Dorota Kazmierczak, David F. Myers, Lawrence R. Roberts, Mark F. Roberts, Richard Sibbick, Denise A. Silva, Riccardo Stoppa, Jeffrey Thomas, Nathan A. Tregger, Li Zhang.
United States Patent |
11,254,611 |
Berodier , et al. |
February 22, 2022 |
Cement production
Abstract
The present invention provides a method and system for
manufacturing cement wherein ground particles of cement and calcium
sulfate are subjected to infrared sensors, laser sensors, or both,
so that emanated, irradiated, transmitted, and/or absorbed energy
having wavelengths principally within the range of 700 nanometers
to 1 millimeter can be monitored and compared to stored data
previously obtained from ground cement and sulfate particles and
preferably correlated with stored strength, calorimetric, or other
data values, such that adjustments can be made to the mill
processing conditions, such as the form or amounts of calcium
sulfate (e.g., gypsum, plaster, anhydride), or cement additive
levels. The strength and other properties of cement can be thus
adjusted, and its quality can be more uniform.
Inventors: |
Berodier; Elise (Lausanne,
CH), Tregger; Nathan A. (Northborough, MA),
Cheung; Josephine H. (Lexington, MA), Myers; David F.
(Somerville, MA), Zhang; Li (Acton, MA), Kazmierczak;
Dorota (Acton, MA), Roberts; Lawrence R. (Acton, MA),
Silva; Denise A. (Los Alamitos, CA), Sibbick; Richard
(Northborough, MA), Thomas; Jeffrey (Winchester, MA),
Roberts; Mark F. (North Andover, MA), Stoppa; Riccardo
(Milan, IT), Burns; Elizabeth (Windham, NH) |
Applicant: |
Name |
City |
State |
Country |
Type |
GCP Applied Technologies Inc. |
Cambridge |
MA |
US |
|
|
Family
ID: |
70461884 |
Appl.
No.: |
16/465,448 |
Filed: |
December 20, 2018 |
PCT
Filed: |
December 20, 2018 |
PCT No.: |
PCT/US2018/066665 |
371(c)(1),(2),(4) Date: |
May 30, 2019 |
PCT
Pub. No.: |
WO2020/091821 |
PCT
Pub. Date: |
May 07, 2020 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20210094876 A1 |
Apr 1, 2021 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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62755102 |
Nov 2, 2018 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N
21/4788 (20130101); B02C 25/00 (20130101); C04B
7/52 (20130101); B02C 17/1815 (20130101); C04B
7/02 (20130101); C04B 7/362 (20130101); G01N
21/3563 (20130101); G01N 21/359 (20130101); B02C
23/22 (20130101); G01N 33/383 (20130101); B02C
17/1805 (20130101); C04B 7/362 (20130101); C04B
7/02 (20130101); Y02P 40/121 (20151101); Y02P
40/10 (20151101); C04B 2103/001 (20130101); C04B
2103/12 (20130101) |
Current International
Class: |
C04B
7/02 (20060101); G01N 21/3563 (20140101); G01N
21/359 (20140101); G01N 21/47 (20060101); G01N
33/38 (20060101); C04B 7/52 (20060101); C04B
7/36 (20060101); B02C 23/22 (20060101); B02C
17/18 (20060101); B02C 25/00 (20060101) |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
|
|
|
|
|
|
|
0463960 |
|
Feb 1992 |
|
EP |
|
0974561 |
|
Jan 2000 |
|
EP |
|
1862795 |
|
May 2006 |
|
EP |
|
1382905 |
|
Sep 2007 |
|
EP |
|
2640499 |
|
May 2012 |
|
EP |
|
111193 |
|
Jun 1983 |
|
GB |
|
9531710 |
|
Nov 1995 |
|
WO |
|
9940419 |
|
Aug 1999 |
|
WO |
|
9946584 |
|
Sep 1999 |
|
WO |
|
9958959 |
|
Nov 1999 |
|
WO |
|
0025115 |
|
May 2000 |
|
WO |
|
0222246 |
|
Mar 2002 |
|
WO |
|
0235213 |
|
May 2002 |
|
WO |
|
03059852 |
|
Jul 2003 |
|
WO |
|
03102574 |
|
Nov 2003 |
|
WO |
|
2004101178 |
|
Nov 2004 |
|
WO |
|
2004106874 |
|
Dec 2004 |
|
WO |
|
2006054154 |
|
May 2006 |
|
WO |
|
2007128832 |
|
Nov 2007 |
|
WO |
|
2007128833 |
|
Nov 2007 |
|
WO |
|
Other References
Wallace, "The Benefit of NIR Spectroscopy in the Production of
Polymers", Polymer Rheology Conference 2001, Paper 16, pp. 1-3.
(Year: 2001). cited by examiner .
Moessner, "Utility of near-infrared analyzers for real-time process
control", Process Control and Quality, 2(1992) 237-247, Elsevier
Science Publishers B.V. Amsterdam. cited by applicant .
Walling & Dabney, "Process control of shampoo with
near-infrared reflectance spectroscopy", Journal of the Society of
Cosmetic Chemists, 39, 191-199 (May/Jun. 1988). cited by applicant
.
Cooper, "NIR Analysis for Process Control", Cereal Foods World
1983, pp. 241-245. cited by applicant .
Wu et al., "Remote in-line monitoring of emulsion polymerization of
styrene by short-wavelength near-infrared spectroscopy / Part I.
Performance during normal runs", Process and Quality 8 (1996),
1-23. cited by applicant .
Fontoura et al., "Monitoring and Control of Styrene Solution
Polymerization Using NIR Spectroscopy", Journal of Applied Polymer
Science, vol. 90, 1273-1289 (2003). cited by applicant.
|
Primary Examiner: Bologna; Dominic J
Attorney, Agent or Firm: Leon; Craig K.
Claims
It is claimed:
1. A method for manufacturing cement, comprising: (A) introducing,
into a grinding mill, raw materials comprising clinker, a source of
sulfate chosen from gypsum, plaster, calcium anhydrite, or a
mixture thereof; grinding the raw materials, to produce a ground
blend of particles comprising ground clinker and calcium sulfate;
and separating the ground blend of particles within a classifier
whereby a first portion of the particles or the finished cement is
removed from the grinding mill and whereby a second portion of the
particles is recirculated for further grinding in the grinding
mill; (B) providing at least one sensor system comprising a
processor that is communicative with processor-accessible memory,
the at least one sensor system chosen from infrared sensor system,
laser diffraction sensor system, or both, and detecting emanation,
reflectance, transmittance, or absorption of energy by or through
the ground blend of particles or finished cement provided in step
(A), and generating output signals corresponding to the detected
energy; (C) comparing, using the processor, the output signals
generated in step (B) to data stored in the processor-accessible
memory, the stored data comprising output signal values previously
obtained from sensors measuring the emanation, reflectance,
transmittance, or absorption of energy in the infrared spectrum,
laser diffraction spectrum, or in both the infrared and laser
diffraction spectrums, the stored data being correlated with a
physical or chemical property of the corresponding finished cement,
hydrated cement, or cementitious product made with the cement; and
(D) in response to the comparison in step (C), adjusting a grinding
mill condition chosen from (i) adjusting amount and form of calcium
sulfate introduced into the grinding mill in step (A); (ii)
adjusting classifier settings thereby to change relative amounts of
ground particles being removed from the grinding mill and being
recirculated back into the grinding mill; (iii) adjusting amount,
type, or both amount and type of cement additives introduced into
the grinding mill; (iv) adjusting amount of water being introduced
into the grinding mill; (v) adjusting amount of air provided by
adjusting power or speed of a fan or blower connected to ventilate
the mill; (vi) adjusting amount or type of supplemental
cementitious material introduced into the grinding mill; or (vii)
performing a combination of the foregoing adjustments of grinding
mill conditions.
2. The method of claim 1 wherein steps (A) through (D) are
performed and repeated on at least a monthly basis or at shorter
time intervals.
3. The method of claim 1 wherein steps (A) through (D) are
performed and repeated for at least successive 100,000 metric tons
(MT) of cement clinker being ground in the grinding mill or at
shorter volume intervals.
4. The method of claim 1 wherein steps (A) through (D) are
performed and repeated upon a detected change in the cement
production process.
5. The method of claim 1 wherein, in step (A), the processor is
programmed to adjust sulfate entering the mill in terms of calcium
sulfate type, feed rate, or both type and feed rate.
6. The method of claim 1 wherein the processor is programmed to
adjust supplementary cementitious materials (SCM) entering the mill
in terms of type, feed rate, or both type and feed rate.
7. The method of claim 1 wherein the processor is programmed to
adjust the introduction of chemical additives into the grinding
mill in terms of type, formulation, amounts, dosage rate, or a
combination thereof.
8. The method of claim 1 wherein the processor is programmed to
adjust a kiln process, a mill process or both.
9. The method of claim 1 further comprising collecting data from at
least one non-IR, non-laser sensor disposed or located within, or
at the inlet or outlet of: (i) the grinding mill, (ii) an air flow
inlet, outlet, or channel connected to grinding mill, or (iii) a
kiln that produces cement clinker material introduced into the
grinding mill.
10. The method of claim 1 further comprising providing an IR or
laser sensor within an elevator bucket, conveyor belt, air slide,
or pneumatic conveying device within or connected to the grinding
mill.
11. The method of claim 1 wherein, in step (C), the data stored is
correlated with a physical or chemical property of finished or
hydrated cement, which physical or chemical property is chosen from
(i) strength test data, (ii) exothermic data; (iii) set initiation
data; (iv) slump data; (v) dimensional stability data; (vi) air
content data; (vii) prehydration data; (viii) reduction or burn
conditions data; (ix) cement fineness data; or (x) a mixture
thereof.
12. The method of claim 1 wherein, in step (B), the at least one
sensor system is an infrared sensor system having an infrared
emitter to irradiate the ground blend of particles or finished
cement and an infrared sensor to detect infrared radiation (IR)
reflected from the irradiated ground blend of particles or finished
cement, the infrared sensor system thereby obtaining reflected IR
data; and, in step (C), the processor compares the reflected IR
data with stored reflected IR data corresponding to strength test
data of hydrated ground blend of particles or finished cement at a
predetermined age.
13. The method of claim 1 wherein, in step (B), the at least one
sensor system is an infrared sensor system having an infrared
emitter to irradiate the ground blend of particles or finished
cement and an infrared sensor to detect infrared radiation (IR)
reflected from the irradiated ground blend of particles or finished
cement, the infrared sensor system thereby obtaining reflected IR
data; and, in step (C), the processor compares the reflected IR
data with stored reflected IR data corresponding to exothermic data
stored in processor-accessible memory.
14. The method of claim 1 wherein, in step (C), the stored
reflected IR data corresponds to exothermic data comprising
calorimetric measurements of hydrating ground finished cement; the
method further comprising: determining whether the difference
between the time T.sub.2 minus time T.sub.1 is less than (-)1 hours
or greater than (+)4 hours, where T.sub.1 represents the time at
which maximum silicate reaction rate occurs after initiation of
cement hydration and T.sub.2 represents the time after initiation
of cement hydration at which either the renewed tricalcium
aluminate reaction rate occurs (if after T.sub.1) or at which the
aluminate reaction is completed (if occurring before T.sub.1); and
if the difference of T.sub.2 minus T.sub.1 is less than (-)1 hours
or greater than (+)4 hours, adjusting the amount of gypsum,
plaster, calcium anhydrite or a combination thereof within the
sulfate source introduced into the grinding mill, adjusting the
sulfate feed rate into the mill.
15. The method of claim 14 further comprising adjusting amount of
water introduced into the mill, power or speed of a fan or blower
connected to ventilate the mill, amount of additive or additives
introduced into the grinding mill; or a combination thereof.
16. The method of claim 1 wherein, in step (C), the stored
reflected IR data corresponds to exothermic data comprising
calorimetric measurements of hydrating ground finished cement; the
method further comprising: determining whether the difference
between the time T.sub.2 minus time T.sub.1 is less than the
predefined target minus 1 hour or greater than the predefined
target plus 2 hour, where T.sub.1 represents the time at which
maximum silicate reaction rate occurs after initiation of cement
hydration and T.sub.2 represents the time after initiation of
cement hydration at which either the renewed tricalcium aluminate
reaction rate occurs if after T.sub.1 or at which the aluminate
reaction is completed if occurring before T.sub.1; and if the
difference is less than the predefined target minus 1 hour or
greater than the predefined target plus 2 hours, adjusting a
grinding mill condition chosen from (i) amount, form or both amount
and form of calcium sulfate introduced into the grinding mill; (ii)
classifier settings, thereby to change relative amounts of ground
particles being sent to the silo and being recirculated back into
the grinding mill; (iii) amount, type, or both amount and type of
cement additives introduced into the grinding mill; (iv) amount of
water being introduced into the grinding mill; (v) amount of air
provided by adjusting power or speed of a fan or blower connected
to ventilate the mill; (vi) amount or type of supplemental
cementitious material introduced into the grinding mill; (vii)
cement cooler setting, thereby to change the temperature of the
finished cement or (viii) a combination thereof.
17. The method of claim 1 wherein, in step (C), the method further
comprises comparing sensor data taken from step (B) to at least two
different stored processor-accessible data sets.
18. The method of claim 1 further comprising measuring the particle
size of the clinker and calcium sulfate being ground in the
grinding mill; and, in further response to the step (C) comparison
between the obtained reflected IR data and the stored reflected IR,
adjusting a particle size characteristic or property of the clinker
and calcium sulfate being ground, or both.
19. The method of claim 1 further comprising the steps of
calculating a value corresponding to degree or level of
prehydration of the cement, incorporating the value into
processor-accessible memory, and initiating decision whether to
adjust at least one of the grinding mill or recirculation
conditions, and, if the decision to adjust grinding mill or
recirculation conditions is initiated, adjusting at least one of
the grinding mill or recirculation conditions.
20. The method of claim 1 wherein, in step (B), the at least one
energy radiation/sensor system is an infrared sensor system having
an infrared emitter to irradiate the ground blend of particles or
finished cement and an infrared sensor to detect infrared radiation
(IR) reflected from the irradiated ground blend of particles or
finished cement, the infrared sensor system thereby obtaining
reflected IR data; and, in step (C), the processor comparing the
reflected IR data with stored reflected IR data corresponding to
test result data, and indicating on a monitor display, by print
out, or by visual or audible alarm indicating the degree of
reduction in the clinker or otherwise that a pre-established
threshold of clinker reduction has been met or exceeded.
21. The method of claim 1 further comprising introducing into the
grinding mill and into the raw materials at least one cement
additive.
22. The method of claim 21 further comprising adjusting amount,
type, or both amount and type of the at least one cement additive
introduced into the grinding mill.
23. A system for manufacturing cement, comprising: a grinding mill
for grinding raw materials including clinker, a source of sulfate
chosen from gypsum, plaster, calcium anhydrite, or a mixture
thereof to produce a ground blend of particles comprising ground
clinker and calcium sulfate; a classifier for separating the ground
blend of particles whereby a first portion of the particles or the
finished cement is removed from the grinding mill and whereby a
second portion of the particles is recirculated for further
grinding in the grinding mill; at least one sensor system
comprising a processor that is communicative with
processor-accessible memory, the at least one sensor system chosen
from infrared sensor system, laser diffraction sensor system, or
both, the sensor system detecting emanation, reflectance,
transmittance, or absorption of energy by or through the ground
blend of particles or finished cement, and the sensor system
effective for generating output signals corresponding to the
detected energy; and the processor configured or programed to
compare output signals generated by the at least one sensor system
with data stored in the processor-accessible memory, the stored
data comprising output signal values previously obtained from
sensors measuring the emanation, reflectance, transmittance, or
absorption of energy in the infrared spectrum, laser diffraction
spectrum, or in both the infrared and laser diffraction spectrums;
and the processor further configured or programmed to perform an
adjustment chosen from (i) adjusting amount and form of calcium
sulfate introduced into the grinding mill (ii) adjusting the
classifier settings thereby to change relative amounts of ground
particles being removed from the grinding mill and being
recirculated back into the grinding mill; (iii) adjusting amount,
type, or both amount and type of cement additives introduced into
the grinding mill; (iv) adjusting amount of water being introduced
into the grinding mill; (v) adjusting the amount of air provided by
adjusting power or speed of a fan or blower connected to ventilate
the mill; (vi) adjusting amount or type of supplemental
cementitious material introduced into the grinding mill; (vii)
performing a combination of the foregoing adjustments of grinding
mill conditions.
24. The system of claim 23 further comprising introducing at least
one cement additive to the raw materials being ground.
25. The system of claim 24 wherein the processor is further
programed to adjust amount, type, or both amount and type of cement
additive introduced into the grinding mill.
26. A method for manufacturing cement, comprising: (A) introducing,
into a grinding mill, raw materials comprising clinker, a source of
sulfate chosen from gypsum, plaster, calcium anhydrite, or a
mixture thereof, and at least one cement additive; grinding the raw
materials, to produce a ground blend of particles comprising ground
clinker and calcium sulfate and the at least one cement additive;
and separating the ground blend of particles comprising the ground
clinker, calcium sulfate, and the at least one cement additive,
within a classifier whereby a first portion of the particles or the
finished cement is removed from the grinding mill and whereby a
second portion of the particles is recirculated for further
grinding in the grinding mill; (B) providing at least one sensor
system comprising a processor that is communicative with
processor-accessible memory, the at least one sensor system chosen
from infrared sensor system, laser diffraction sensor system, or
both, and detecting emanation, reflectance, transmittance, or
absorption of energy by or through the ground blend of particles or
finished cement comprising the ground clinker, calcium sulfate, and
the at least one cement additive, as provided in step (A), and
generating output signals corresponding to the detected energy; (C)
comparing, using the processor, the output signals generated in
step (B) to data stored in the processor-accessible memory, the
stored data comprising output signal values previously obtained
from sensors measuring the emanation, reflectance, transmittance,
or absorption of energy in the infrared spectrum, laser diffraction
spectrum, or in both the infrared and laser diffraction spectrums,
the stored data being correlated with a physical or chemical
property of the corresponding finished cement, hydrated cement, or
cementitious product comprising the ground clinker, calcium
sulfate, and the at least one cement additive; and (D) in response
to the comparison in step (C), adjusting amount, type, or both
amount and type of the at least one cement additive introduced into
the grinding mill.
27. The method of claim 26 further comprising, in Step (D) response
to the comparison in step (C), adjusting a grinding mill condition
chosen from adjusting the amount and form of calcium sulfate
introduced into the grinding mill in step (A); adjusting classifier
settings thereby to change relative amounts of ground particles
being removed from the grinding mill and being recirculated for
further grinding in the grinding mill; adjusting amount of water
being introduced into the grinding mill; adjusting amount of air
provided by adjusting power or speed of a fan or blower connected
to ventilate the mill; adjusting amount or type of supplemental
cementitious material introduced into the grinding mill; or
performing a combination of the foregoing adjustments of grinding
mill conditions.
Description
FIELD OF THE INVENTION
The invention relates to cement manufacturing; and, more
particularly, it relates to monitoring and adjusting of calcium
sulfate and cement additives in a cement grinding mill to optimize
strength of the ground cement.
BACKGROUND OF THE INVENTION
Cement-based materials, such as concrete and mortar, are among the
most widely used construction materials in the world, as they are
necessary for making roads, bridges, tunnels, foundations,
buildings, dams, and other infrastructure. The manufacture of
cement and the study of its impact on cement hydration and material
strength, however, involve heterogeneous factors that give rise to
complex issues.
FIG. 1 illustrates a typical process whereby clinker is made and
ground in a mill to provide cement, which is the binder material
for concrete and mortar. Raw materials containing calcium, iron,
silicon and aluminum (designated at 2), are crushed and blended
(4), stored (6), optionally preheated (8), and fed into the kiln
(10), where they are heated to very high temperatures (e.g.,
1500.degree. C.). Heating in the kiln is sufficient to fuse the raw
materials into clinker "nodules" which are cooled or allowed to
cool (12) and are optionally stored (14). The clinker nodules are
added with a source of calcium sulfate (16) and fed into the cement
mill (18) which grinds the materials to produce the finished cement
(20).
Supplemental cementitious materials, such as fly ash, slag, other
pozzolans, and/or limestone, may be added with the clinker before
(at 16) or after the grinding mill stage (18). The produced cement
is typically cooled and then tested (20), stored in silos (22)
until being delivered to the customer (22), who uses the cement to
make concrete, mortar, or other construction materials.
Typically, sulfate, in the form of gypsum, is added into the cement
mill (18), where the clinker and gypsum are ground to a specific
particle size (20). The resultant ground particles of clinker, and
gypsum are commonly referred to as Portland cement. Blended cements
are Portland cements combined with supplementary cementitious
materials (e.g., fly ash) before or after the mill.
The manufacture of Portland cement generates a significant amount
of carbon dioxide. This occurs especially during firing of the kiln
(10) where calcination of the limestone occurs (releasing carbon
dioxide). For each metric ton of cement produced, approximately
0.84 tons of carbon dioxide are released (See e.g., WBCSD Cement
Sustainability Initiative reports). As annual production is about 4
billion metric tons of cement, this amount represents approximately
5% of all carbon dioxide generated by man-made processes. Reducing
carbon dioxide is of great importance to sustainability initiatives
in cement production.
It can be difficult to obtain consistent quality in cement products
despite expensive process controls. Major reasons include high
variability of the raw materials (due to their origin within a
given quarry as well as across multiple quarries) and of processing
conditions--such as kiln temperature, oxygen levels within the
kiln, rate of cooling, and kiln fuel changes that can affect the
interaction of chemical constituents as the clinker is formed.
The present inventors believe that improving control over cement
hydration, despite numerous factors that fluctuate during
manufacturing, such as aluminate content and sulfate availability,
provides many benefits. They propose to implement monitoring and
adjustment processes not currently used or envisioned today in the
cement manufacturing field, so that greater consistency of cement
product quality can be realized.
By focusing on consistency by accounting for the variation in
clinker, sulfate and other materials introduced into the cement
mill as well as the grinding process conditions, the present
inventors believe that they can enhance the consistency of strength
in the cement product, as well as reduce its large carbon
footprint.
Furthermore, the inventors believe that the performance of cement
additives can also benefit by accounting for variation in the
clinker and other materials introduced into the cement mill as well
as the grinding process conditions. Cement additives are chemical
products used to improve the efficiency of cement grinding mills
(grinding aids) and/or to improve the performance of mortars and
concretes made with the cement (quality improvers). One such
performance parameter is cement compressive strength. Cement
additives are often used to increase the strength of the cement at
one or more ages. FIG. 2 shows some typical response curves of
compressive strengths obtained by using the testing methods
described in EN-196-1:2016 on mortars as a function of two strength
enhancing chemicals commonly used in cement additives. As can be
seen, different cement additives have different optimum dosage
requirements with respect to achieving optimum cement strength (in
this case 1 day compressive strength). Typically, the dose of a
cement additive is determined based on the production parameters of
the mill (such as mill output) and quality parameters of the cement
(such as fineness, residue in the "#325 sieve", powder flow,
pack-set, set time, rheological behavior, and compressive
strength). Most plants are equipped with flowmeters that allow
accurate monitoring of the volume of cement additive being
introduced in the mill. Cement additives can be used to further
reduce the inconsistencies and to improve the quality of the
cement. Knowledge of the variations can allow cement additives to
be adjusted in type or amount, with a variety of goals including,
but not limited to, maximizing strength, achieving a target early
age strength without exceeding a later age maximum, increasing the
use of supplementary cementitious materials, controlling set time
or rheology, and other advantages. Thus, within a closed-loop
framework, additives can be used to increase consistency of the
final cement product.
Ground Portland cement is primarily composed of hydratable calcium
silicates. The calcium silicates are essentially a mixture of
tricalcium silicate (otherwise referred to as alite,
3CaO.SiO.sub.2, or "C.sub.3S" in cement chemists' notation) and
dicalcium silicate (otherwise referred to as belite,
2CaO.SiO.sub.2, or "C.sub.2S") in which the former is the dominant
form, with lesser amounts of tricalcium aluminate
(3CaO.Al.sub.2O.sub.3, "C.sub.3A") and tetracalcium aluminoferrite
(4CaO.Al.sub.2O.sub.3.Fe.sub.2O.sub.3, "C.sub.4AF"). See e.g.,
Dodson, Vance H., Concrete Admixtures (Van Nostrand Reinhold, New
York N.Y. 1990), page 1.
In order to control the early calcium aluminate reaction, cement
manufacturers typically add an amount of sulfate, often in the form
of gypsum, to the cement clinker. It is the sulfate which, upon
contact with water when mixed with cement (e.g., to make concrete
or mortar), reacts with calcium aluminate to form a hydrated
product called ettringite. This reaction consumes aluminates and
thus lowers aluminum concentration in solution, which allows proper
formation of the calcium silicate hydrates (C--S--H) and thereby
confer strength to the concrete or mortar made from the cement.
The present inventors shall use calcium sulfate as an example of a
"source of sulfate" which will be introduced into a grinding mill
along with clinker to produce cement. Gypsum (i.e., calcium sulfate
dihydrate) is a form of calcium sulfate that reacts readily with
calcium aluminate in the cement during hydration. Other forms of
calcium sulfate are "plaster" (e.g., calcium sulfate hemihydrate,
or bassanite), and calcium sulfate anhydrite. Thus, gypsum is 1
mole of calcium sulfate associated with 2 moles of water
(Ca.sub.2SO.sub.4.2H.sub.2O); plaster is 1 mole of calcium sulfate
associated with 0.5 moles of water (Ca.sub.2SO.sub.41/2H.sub.2O);
and anhydrite is calcium sulfate that is not associated with water
(Ca.sub.2SO.sub.4).
The hemihydrate form of calcium sulfate (plaster) is also relied
upon as a calcium sulfate source in the cement plant to control the
aluminate reaction. The advantage of using hemihydrate is due
mainly to its faster solubility in water. Although plaster is
rarely added as a source of sulfate directly into the mill, varying
amounts of calcium sulfate hemihydrate are present in the finished
cement as a result of the dehydration of gypsum (the dihydrate
form). This dehydration is prompted by high temperatures (e.g.,
above 100.degree. C.) in the grinding mill environment that tend to
evaporate water from gypsum and convert it into plaster.
In spite of attempts to control temperature and relative humidity
conditions in the milling system, cement plant owners are not
readily equipped to control precisely the amount of plaster being
transformed from gypsum within the grinding process. This
transformation is commonly seen in ball mill systems that readily
generate heat; but not typically seen in vertical roller mills
(VRMs) wherein the temperature of the mill is typically lower than
the dehydration temperature of the gypsum, and additionally, the
humidity is relatively higher, due primarily from water being added
to stabilize the VRMs. Both conditions lead to decreased
dehydration of gypsum to plaster.
Calcium sulfates can react with the aluminate phases to form
ettringite, thus decreasing calcium aluminate hydration that
otherwise decreases workability and strength of the cement.
Although calcium sulfates can balance the aluminate reaction by
keeping the sulfate concentration high enough to limit aluminate
reactions in advance of the silicate reactions to prevent flash set
and poor strength development (through hindrance of the calcium
silicate reaction), a number of generally accepted standards in the
industry (e.g., ASTM C1157, EN 197-1:2011) impose limits on total
sulfate content. Such standards impose limits on the maximum amount
of sulfate in cements under the theory that excessive sulfate
levels give rise to detrimental expansion and false setting of
cements. Other standards have evolved to permit higher sulfate
levels as long as deleterious expansion is avoided (e.g. ASTM
C150/C150M-18 does not limit the sulfate as long as tests under
ASTM C1038/C1038M-14b do not demonstrate deleterious
expansion).
Thus, an optimum amount of sulfate is desired to control the
calcium aluminate reaction while maintaining performance factors
such as strength, workability shrinkage, and expansion.
Despite the importance of adding the optimum amount of sulfate,
testing for optimum sulfate levels in the grinding mill is
typically done on an infrequent basis. Strength testing requires at
least 24 hours, while calorimetric testing requires 8-24 hours. See
e.g., Sandberg, P. "The use of isothermal calorimetry in cement
production,"
http://downloads.calmetrix.com/Downloads/CCW2016/Paul_Sandberg_The_use_of-
_Isothermal_calorimetry_in_cement_production.pdf).
Given that large cement plants can produce 10,000 metric tons (MT)
of cement every day, the present inventors believe that processing
conditions (e.g., quality and ratio of raw materials fed into the
kiln (10), the fuel used for heating the kiln, and other factors)
present too many variables for the typical cement manufacturer to
consider at present time.
The present inventors believe that a consistent quality of cement
cannot be attained by adjusting sulfate levels annually,
semi-annually or even monthly, because variations in the clinker
over shorter time increments can alter the ideal sulfate level for
reaching maximum strength at a given age of the cement.
In preparing for summary of the present invention, which culminates
in the next section, the present inventors describe specific
difficulties in testing the relationship between sulfate levels and
optimum strength in cement, as well as current practices which have
tended to mask discovery and resolution of those difficulties to
this point in time.
FIG. 3A illustrates compressive strength data (at 1 day age) for
cement containing various amounts of gypsum (dihydrate form). The
gypsum is added incrementally into ground cement clinker in
accordance with ASTM C563-17, and is dosed as a percentage of the
cement mass. The cement made from variously dosed gypsum levels is
used to form mortar test samples, which are crushed to obtain
compressive strength values, in accordance with ASTM C109/109M-16a
or EN-196-1:2016. The results shown in FIG. 3A are made in
accordance to EN-196-1:2016.
The strength curve data of FIG. 3A suggests that the cement has
optimum 1 day compressive strength when sulfate (in the form of
gypsum) is added to the cement clinker in the amount of 1.5%-2.0%
based on weight of cement.
Compared to compressive strength testing, calorimetric testing of
cement samples using varying amounts of sulfate is undoubtedly more
convenient. FIG. 3B graphically illustrates cumulative heat output
testing, over a period of 24 hours, of hydrating cement samples
containing gypsum (the dihydrate form) in varying amounts.
According to the data illustrated in FIG. 3B, the optimum sulfate
content (gypsum) for achieving maximum cumulative exothermic value
in the cement is approximately 1.5%-2.0% based on the weight of the
cement, essentially giving the same result as the compressive
strength tests.
The present inventors note that, to this point in time, a process
manager or the quality control manager of a cement clinker grinding
mill would typically determine optimum sulfate content using a
procedure such as the one described in ASTM C563-17. A small number
of mortar samples with varying amounts of gypsum are formed into
test samples which are crushed to obtain strength data (e.g., ASTM
C109/109M-16a, EN-196-1:2016). FIG. 3C illustrates a typical four
point curve using this conventional method. A mill operator might
estimate, using such a small number of samples (for compressive
strength testing or for calorimetric testing) that the optimum
amount of sulfate (e.g., gypsum), for example, is 1.75% based on
weight of cement. Based on this data, the mill operator would tend
to set the level of gypsum addition in the mill at this amount for
an extended amount of time, (e.g. the next 12 months).
However, the present inventors believe this conventional approach
does not guarantee optimum strength because clinker components,
kiln fuel, as well as the form or amount of sulfate likely
fluctuate over the 12 month period and potentially on the daily and
hourly periods. They also believe that optimum strength of the
cement cannot be achieved consistently based on this conventional
practice.
As explained in the background, the present inventors realize that
the heat of the mill conditions could transform gypsum (dihydrate
form) to the plaster form, which is more soluble (hemihydrate
form). They also realize that the humidity levels in and around the
mill could fluctuate greatly throughout any extended period of
time, such that the amount of rapidly available sulfate could
fluctuate.
Indeed, the present inventors believe that the amount of sulfate
contained in the clinker itself, an amount of sulfate which albeit
is typically small, can vary substantially and become a factor
influencing strength of the cement at some point within any
extended period of time (e.g. 12 months).
The present inventors believe that mill operators do not usually do
multi-point compressive strength or calorimetry testing with enough
frequency to obtain useful information regarding sulfate content
and relative strength at certain ages; and that they do not
routinely consider the myriad process conditions that change from
moment to moment and that affect cement properties.
Although it is possible in a laboratory setting to measure sulfate
levels in cement using X-Ray Diffraction (XRD) or X-Ray Florescence
(XRF) after the cement is ground, there is no method to calculate
the optimum gypsum (calcium sulfate dihydrate) or plaster (calcium
sulfate hemihydrate) content based on XRF or XRD data.
Furthermore, there is no method that is used in the cement industry
for adjusting the amount of dihydrate and hemihydrate forms of
calcium sulfate to obtain optimum strength for certain cement ages.
As a result, cements being produced today can demonstrate large
fluctuations in terms of quality (e.g. set time and strength),
despite investments in quality control systems by the cement
manufacturers.
Cement manufacturers have attempted to mitigate the risks stemming
from the variabilities of cement production by "overdesigning"
their cement products. For example, this might be done by using
more clinker and less supplemental cementitious materials (e.g.,
fly ash, slag) or by grinding cement particles to finer Blaine
specific surface areas to increase the average compressive strength
and make it less likely that strength fluctuation result in the
cement not meeting specification. In either case, these approaches
involve higher carbon dioxide generation (due to clinker kiln
operation or milling electricity) and are not energy efficient.
Concrete producers also have used more cement to overcome
inconsistent strength performance. Up to twenty percent extra
cement might be used to ensure that strength targets are met. This
again means more carbon dioxide is generated due to the greater
demand for cement.
SUMMARY OF THE INVENTION
In surmounting the disadvantages of prior art approaches, the
present invention addresses several issues in providing a method
and system for optimizing sulfate and cement additive levels,
cement fineness and other factors to attain target strength (at
certain ages) or other performance targets when the cement is
hydrated.
The present inventors take into consideration that (A) clinker
components vary (e.g., ratio of calcium (from limestone), iron,
silica, aluminate); (B) nature and type of kiln fuel varies (e.g.,
coal, municipal waste, recycled tires, etc.); (C) kiln conditions
vary (e.g. oxygen levels, flame length, etc.); and that (D) the
amount of available sulfate can vary due to the hydration state of
calcium sulfate being introduced into the grinding mill. For
example, gypsum can dehydrate into plaster due to the hot
environment of the grinding mill, whereby the calcium sulfate is
rendered more soluble; and, hence, sulfate is more rapidly
available for use in balancing the aluminate reactions.
As illustrated in FIG. 3D, cements ground from three different
clinkers, having different components and/or component ratios, are
shown to require different sulfate contents (added as gypsum) to
achieve a maximum 1-day strength. The present inventors believe
this type of behavior can be found not only across various cement
plants, but also within the individual manufacturing process of a
single cement plant over a relatively short period of time.
Likewise, FIG. 4 shows the responses of three different cements
(C1, C2, C3) to the addition of a given cement additive. FIG. 4
illustrates that the impact of cement additives on the strength of
a cement depends on several characteristics of the cement that
include its chemical and mineralogical composition and its physical
properties. In this case, the Blaine specific surface area, which
is an indication of the surface area of the cement, is held
constant. Even as such, the differences in C1, C2 and C3 are a
result of the respective clinker chemistry differences.
In summary, any given cement plant can have a significant
fluctuation in the raw materials, kiln fuels and kiln operating
conditions used for making cement clinker. Given this scenario, the
present inventors believe that a mill owner (cement manufacturer)
must not simply perform strength or calorimetric testing
infrequently (e.g. just once a year) and rely on those test results
for an extended period of time to make cement with a consistent
quality.
Aside from frequent monitoring of the optimum sulfate, the present
inventors also believe that the amount and form of calcium sulfate
existing in the cement should be monitored and adjusted on a
frequent basis, as this would help to minimize variation in the
quality and performance of the cements. More preferably, the
relative amounts of both calcium sulfate dihydrate (gypsum) and
calcium sulfate hemihydrate (plaster) should be monitored and
adjusted on a frequent basis. Doing so would permit a mill operator
to take into consideration the effect of various changing
environmental conditions, including plant and storage conditions,
which can affect the source of calcium sulfate and levels of
soluble sulfate available to control the aluminate balance, which,
in turn, can affect cement performance.
Accordingly, in an exemplary embodiment, the present invention
provides a method for manufacturing cement, comprising:
(A) introducing, into a grinding mill, raw materials comprising
clinker, a source of sulfate chosen from gypsum, plaster, calcium
anhydrite, or a mixture thereof, and optionally one or more
supplemental cementitious materials and optionally at least one
cement additive; grinding the raw materials, to produce a ground
blend of particles comprising ground clinker and calcium sulfate;
and separating the ground blend of particles within a classifier
whereby a first portion of the particles or the finished cement are
sent to a silo or other receptacle for containing the finished
cement and whereby a second portion of the particles is
recirculated into the grinding mill for further grinding;
(B) providing at least at least one sensor system chosen from
infrared sensor system, laser diffraction sensor system, or both,
and detecting emanation, reflectance, transmittance, or absorption
of energy by or through the ground blend of particles or finished
cement provided in step (A), and generating output signals
corresponding to the detected energy;
(C) comparing output signals generated in step (B) to data stored
in processor-accessible memory, the stored data comprising output
signal values previously obtained from sensors measuring the
emanation, reflectance, transmittance, or absorption of energy in
the infrared spectrum, laser diffraction spectrum, or in both the
infrared and laser diffraction spectrums, the stored data being
correlated with a physical or chemical property of the
corresponding finished cement, hydrated cement, or cementitious
product made with the cement; and
(D) in response to the comparison in step (C), adjusting (i)
amount, form or both amount and form of calcium sulfate introduced
into the grinding mill in step (A); (ii) classifier settings,
thereby to change relative amounts of ground particles being sent
to the silo and being recirculated back into the grinding mill;
(iii) amount, type, or both amount and type of cement additives
introduced into the grinding mill; (iv) amount of water being
introduced into the grinding mill; (v) amount of air provided by
adjusting power or speed of a fan or blower connected to ventilate
the mill; (vi) amount or type of supplemental cementitious material
introduced into the grinding mill; (vii) cement cooler setting,
thereby to change the temperature of the finished cement or (viii)
combination of any of the foregoing.
In further exemplary methods of the present invention, the amount
and form of sulfate can be adjusted by taking into account (A) the
total amount of calcium sulfate (i.e. gypsum, plaster and
anhydrite) as well as (B) the ratios between each of the different
forms monitored in the ground blend of particles or finished
cement, and to adjust both (A) and (B) on a periodic basis. For
example, monitoring and adjustment can occur monthly intervals or
less.
In still further exemplary methods, the present inventors believe
that even further advantages may be achieved through monitoring and
adjusting the source of calcium sulfate (i.e., amount and/or form)
in the ground blend of particles or finished cement on a more
frequent basis, such as hourly, more preferably every fifteen
minutes, and most preferably at an interval less than or equal to 5
minutes.
In still further exemplary methods of the present invention, the
amount and type of chemical additive introduced into the mill can
be adjusted on a periodic basis based on the monitoring and
analysis of the ground blend of particles or finished cement.
The present invention also provides a cement grinding system which
is configured to accomplish the exemplary method as described in
the preceding paragraph. The cement grinding system comprises a
mill and at least one IR sensor for monitoring sulfate levels in
particles ground in the mill, the at least one IR sensor being in
communication with a processor configured or programmed to monitor
IR wavelengths reflected from particles ground in a cement grinding
mill.
Further advantages and features of the invention will be discussed
further hereinafter.
BRIEF DESCRIPTION OF DRAWINGS
An appreciation of the benefits and features of the invention may
be more readily appreciated when the various sections of this
specification are considered in conjunction with the drawings.
FIG. 1 is a flow diagram illustration (PRIOR ART) of clinker kiln
and cement mill in the manufacture of cement (as discussed in the
Background section).
FIG. 2 is a graph illustration of 1 day compressive strength of two
cements as a function of varying levels of cement additives (as
discussed in the Background section).
FIGS. 3A, 3B, and 3C are graph illustrations of data points
obtained using conventional methods for optimizing sulfate levels
in cement (as discussed in the Background section).
FIG. 3D is a graph illustration of one-day compressive strength as
a function of varying levels of total sulfate in three cements (as
discussed in the Summary section).
FIG. 4 is a graph illustration of varied performance when using the
same cement additive in three different cements having same Blaine
specific surface area (as discussed in the Background section).
FIGS. 5A through 5E are graph illustrations of exothermic heat
value (heat flow) as a function of time in five different samples
of hydrating cement, demonstrating peak exothermic values
corresponding to peak C.sub.3S reaction and the visible onset of
the renewed or completed C.sub.3A reaction in the cement.
FIG. 6A is a graph illustration of one-day compressive strength as
a function of exothermic values (cumulative heat) over 24 hours
after water has been mixed into three cements to hydrate the
cements, where the maximum strength for each cement is designated
by the square symbol.
FIG. 6B is a graph illustration of one-day compressive strength as
a function of the difference in the peak exothermic values which
correspond to C.sub.3S and C.sub.3A dissolution in three cements,
where the maximum strength for each cement is designated by the
square symbol.
FIG. 7 is a graph illustration demonstrating weight loss over time
and the derivative of the weight loss with respect to temperature
for a cement sample obtained using a thermogravimetric analysis
instrument. The cement sample is exposed to a temperature ramp from
22.degree. C. to 450.degree. C.
FIG. 8 is a flow chart of an exemplary method of the present
invention.
FIG. 9 is a diagram illustration of an exemplary system of the
present invention.
FIGS. 10A through 10D are graph illustrations of the relationship
of infrared (IR) light intensity (obtained from cement samples) as
a function of IR wavelength, and their derivatives.
FIG. 11 is a graph illustration demonstrating the prediction
accuracy of a model that receives an NIR signal spectra and that
provides a predicted optimum Delta value, wherein the data plot
confirms a one-to-one correlation (illustrated by the solid
straight line) across a wide range of clinker chemistries and
Blaine specific surface areas.
FIG. 12 is a graph illustration demonstrating the prediction
accuracy of a model that receives an NIR signal spectra and that
provides a predicted Delta value, wherein the data plot confirms a
one-to-one correlation (illustrated by the solid straight line)
across a wide range of clinker chemistries and Blaine specific
surface areas.
FIG. 13 is a graph illustration demonstrating the prediction
accuracy of a model that receives an NIR signal spectra and outputs
a predicted 1 day strength value, wherein the data plot confirms a
one-to-one correlation (illustrated by the solid straight line)
across a wide range of clinker chemistries and Blaine specific
surface areas.
FIG. 14 is a graph illustration demonstrating the improved
prediction accuracy of a model that receives an NIR signal spectra
and outputs a predicted 1 day strength value, wherein the data
confirms a one-to-one correlation (illustrated by the solid
straight line) for a single clinker chemistry.
FIG. 15 is a graph illustration demonstrating the improved
prediction accuracy of a model that receives an NIR signal spectra
and outputs a predicted 1 day strength value, wherein the Delta is
between 1.5 and 2.5 hours, and, furthermore, wherein the data plot
confirms a one-to-one correlation (illustrated by the solid
straight line).
FIG. 16 is a graph illustration demonstrating the compressive
strength response of Cement 1 sulfated at three different levels
and exposed to four levels of a cement additive comprising
Na.sub.2-EDG.
FIG. 17 is a graph illustration demonstrating the compressive
strength response of Cement 2 sulfated at two different levels and
exposed to four levels of a cement additive comprising DEIPA.
FIG. 18 is a graph illustration demonstrating the compressive
strength response of Cement 3 sulfated at two different levels and
exposed to four levels of a cement additive comprising DEIPA.
FIG. 19 is a graph illustration demonstrating the compressive
strength response of Cement 4 sulfated at two different levels and
exposed to four levels of a cement additive comprising DEIPA.
DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS
As used herein, the term "cement" means and refers to hydratable
cement, such as Portland cement, which is produced by grinding
clinker consisting of hydraulic calcium silicates, aluminates, and
aluminoferrites, and one or more forms of calcium sulfate (e.g.,
gypsum) as an interground addition. Frequently, Portland cement is
combined with one or more supplemental cementitious materials as
well as cement additives, and provided as a blend, all of which
binds aggregates together to make a mortar or concrete.
The term "cement additive" means and refers to a chemical product
of organic and/or inorganic nature that is added during the
manufacture of cement either into the grinding mill, at the
entrance of the separator or at the separator exit. Cement
additives comprising grinding aids will primarily reduce the
agglomeration of fine particles during the grinding process, and as
a result, will increase the efficiency of the grinding mill. Cement
additives comprising quality improvers or strength enhancers will
primarily increase the strength of the cement during hydration.
Strength can be enhanced at early ages (e.g. 1 day) or later ages
(e.g. 28 days), and intermediate ages as well. Some chemical
additives provide both early and later age strength enhancements.
Frequently, chemical additives provide some level of both grinding
enhancement and strength enhancement. Cement additives also refer
to any chemical added during the cement manufacturing process that
enhances any property of the cement such as, but not limited to:
set time, shrinkage, expansion, workability, concrete admixture
compatibility, etc.
The term "concrete admixture" means and refers to chemicals added
during the manufacture of concrete.
As used herein, the phrase "supplemental cementitious materials"
means and includes fly ash, silica fume, granulated blast furnace
slag, limestone, clay, calcined clay, natural pozzolans, or
mixtures thereof ("SCM"). These SCMs by themselves often have
little or no cementitious properties, but, when blended with
Portland cement and mixed with water, the blended cement and SCMs
can bind aggregates together to make mortar, concrete, or other
hydratable cementitious compositions.
The term "aggregate" means and refers to sand and/or stone (or
crushed gravel) particles, typically having average size of 0.5 to
50 mm. Aggregates may also comprise calciferous, siliceous or
siliceous limestone minerals. Such aggregates may be of either the
"natural" type (e.g., derived from glacial, alluvial, or marine
deposits which are typically weathered such that the particles have
smooth surfaces) or may be of the "manufactured" type, which are
made using mechanical crushers or grinding devices. Coarse
aggregate stone particles are typically grouped into various size
fractions as described for instance in ASTM C33-16e. As the size
fraction used is controlled by various factors, such as the space
between reinforcing bars in a proposed construction, aggregate size
is often considered in concrete mix designs. The term "aggregate"
may also be used to refer to crushed returned concrete (e.g.
"recycled aggregate").
As used herein, the term "mortar" will refer to a mixture of cement
and optionally supplemental cementitious materials such as
limestone, fly ash, granulated blast furnace slag and other
pozzolanic materials, water, and fine aggregates (e.g., sand). The
term "concrete" is a mortar further containing a coarse aggregate,
such as gravel or crushed stone. Mortars and concretes may
optionally contain one or more chemical admixtures for modifying
the hydratable cementitious composition in its plastic or hardened
state (e.g., plasticizers for increasing workability, set
accelerators, set retarders, air entrainers, air detrainers,
plastic shrinkage reducing admixtures, corrosion inhibitors (for
steel reinforcing bars within the concrete)).
As used herein, the phrase "a source of calcium sulfate" means and
includes gypsum, plaster, and the anhydrite form of calcium
sulfate. The term "gypsum" refers to the dihydrate form of calcium
sulfate. Gypsum occurs as a natural mineral or by-product from
industries. When subjected to sufficient heat, gypsum (more
precisely CaSO.sub.4.2H.sub.2O) dehydrates to form calcium sulfate
hemihydrate (CaSO.sub.4.0.5H.sub.2O) also known as "plaster." The
mineral form of calcium sulfate hemihydrate is called bassanite.
The complete dehydration produces calcium sulfate anhydrite
(CaSO.sub.4). Natural gypsum sources may contain impurities from
other mineral such as quartz, calcite, dolomite, anhydrite, clays
from deposits. The "gypsum" used in cement plants can also be
obtained from chemical by-products such as phosphorgypsum (or
phosphogypsum) from phosphoric acid manufacture, fluorogypsum from
hydrofluoric acid manufacture, formogypsum from formic acid
manufacture, desulphogypsum (or FGD.TM. brand gypsum) from flue gas
desulphurization, etc. By-product gypsum can contain impurities
that can affect the cement performance. Calcium sulfate dihydrate
is commonly added to Portland cement clinker to control the set
time and strength development of the cement.
At the optimum sulfate level for the particular cement, the rate of
aluminate reactions are slowed in order to minimize their
interference with the silicate reactions, thus allowing the
strength of the cement to be optimized.
As used herein, the term "undersulfated" means that the level of
sulfate added to the cement is below the optimum sulfate required
to maximize the cement strength. Furthermore, severely
undersulfated cement could cause "flash setting," referring to
rapid loss of workability, large heat release, and dramatic loss of
early strength development. In other cases, the undersulfated
condition can lead to extended set and low strength gain
development and poorer slump retention. Undersulfated conditions
can also lead to problems with admixture performance, in part due
to absorption of the admixture into certain hydrating aluminate
phases.
As used herein, the term "oversulfated" means that the level of the
sulfate added to the cement is above the optimum sulfate required
to maximize the cement strength. Amounts greater than that required
to prevent the aluminates from interfering with the silicate
hydrations do not help. Strength will go down further sulfate is
added, sometimes sharply.
A second condition exists relative to higher sulfate levels, known
as false set. This occurs when gypsum is dehydrated to form plaster
(which dissolves faster), and there is relatively low aluminate
activity to use of the sulfate that has dissolved. In this case,
the plaster reforms into gypsum as crystals which physically lower
the workability of the hydrating cement, generally in the first few
minutes. While this does not directly impact the strength, addition
of water to overcome the reduced workability results in a overall
lower strength.
As used herein, the term "hydration" means and refers to the
hydration of Portland cement which is a sequence of overlapping
chemical reactions between clinker components, calcium sulfate and
water, leading to setting and hardening. Cement hydration is most
typically studied using a calorimeter to monitor heat released
during hydration. Isothermal calorimetry is a particularly useful
way to follow the progression of the cement hydration, which is the
result of several simultaneous exothermic reactions. The major
chemical reactions between clinker components and calcium sulfate
in the cement, and water initiate the hydration process after water
is mixed with the cement. The words "hydrated" or "hydration" may
include the fact that cement is still curing or increasing in
strength (e.g., compressive strength) over time.
In the cement and concrete industries, it is an understanding that
Ordinary Portland cement (OPC) "prehydrates" during storage or
handling in moist environments, forming hydration products on or
near its particles' surfaces. Thus, the term "prehydration" is
something of an oxymoron, since what is being referred to is
unwanted hydration (or water bonding or reacting at the surface of
cement particles) prior to the time at which the cement is used in
concrete and mortar in combination with water and hardened into a
mass or structure. Again, the term "prehydration" means and refers
to an undesirable reaction between soluble components of cement (or
its various phases) and moisture absorbed onto the surface of the
cement particles either from liquid water or directly from the
vapor phase that occurs before the cement is made into mortar or
concrete upon mixing with hydration water (in amount sufficient to
initiate hydration whereby concrete hardens into rock-like mass or
structure). The level of prehydration of the cement can be
quantitatively measured, for example, using analytical methods
whereby the amount of water that is chemically bound to the
particle surface is ascertained. Further detailed explication
follows below.
Prehydration changes the surface of the cement particles, limiting
the rate of dissolution which leads to a delay of setting, strength
development and poorer flow properties. The surface change can also
interfere with the action of chemical additives, rendering them
less effective in some cases. Thus, it may be difficult to mitigate
effects of prehydration reactions set time by using accelerators,
for example. It is only necessary that a very small fraction (much
less than 1%) of water taken up relative to cement mass will lead
to negative effects at a later stage.
The most common adjustment made by cement plants in response to
prehydration due to surface water reactions is to grind the cement
particles to a higher fineness, to offset strength loss that
typically occurs. This has well-known disadvantages, however, such
as increased energy consumption, decreased throughput, and
increased water demand for the finished cement. In summary, the
prehydration of the cement can have quite significant effects on
the properties of the cement once it is used to make concrete or
mortar, and mitigating these effects after the prehydration
reactions have occurred can be difficult.
Prehydration of the cement can be measured by heating a cement
sample and measuring the weight loss within a defined temperature
range. The level of prehydration reactions on the cement particle
surfaces is most accurately measured using a thermogravimetric
analysis (TGA) instrument. The amount or level of prehydration
reactions on the cement particle surfaces is quantified for the
present purposes as the parameter Wk, defined as the percentage
mass loss of a cement sample as it is heated, starting at a
temperature just after the completion of the gypsum dehydration and
finishing at a temperature just before the calcium hydroxide
(portlandite) starts to decompose. Chemically bound water starts to
be released at temperatures as low as 60.degree. C. and can
continue until temperatures as high as 600.degree. C. The Wk
parameter measures the chemically bound water in a region of the
weight loss versus temperature curve where only strength-giving
clinker phases are dehydrating. At lower temperatures, there is
also the dehydration of the added calcium sulfate phases and
release of physically bound water; at higher temperatures, there is
also the dehydration of calcium hydroxide from free lime and
decarbonation of carbon-containing phases.
As used herein, the term "age" as it is used with respect to a
cementitious composition refers to the time elapsed since the
moment that water is mixed into the cement, mortar, or concrete to
initiate the hydration of the cement, whereby the cement (when used
to produce concrete) is hardened into a mass or structure. For
example, strength properties may be measured at 1, 2, 3, 7, and/or
28 days (or at other "ages") after mixing with water. Different
ages may have significance for different cement producers, and thus
an optimum sulfate may refer to the sulfate required to optimize
strength at a given age (e.g. 1 day, 28 days, etc.).
The major chemical reactions in cement during hydration are
commonly identified in terms of five kinetic stages, as follows.
These stages are most commonly observed via isothermal or
semi-adiabatic colorimetry. Stage 1 represents primarily the rapid
dissolution of clinker interstitial phases (including an initial
dissolution of a fraction of the C.sub.3A) and formation of
ettringite or other aluminate reaction products. Hemihydrate
dissolves, and gypsum or syngenite may form. Stage 2 is known as
the induction period, which is characterized by a slowdown of the
heat released. Stage 3 corresponds to the acceleration period when
silicate hydrates begin to form i.e. C--S--H and CH. Stage 4 is
characterized by the slowdown of the heat, which becomes even lower
at the Stage 5. Although all cements hydrate when mixed with water,
each stage of hydration can have a different rate, depending on
multiple parameters, including but not limited to: cement
chemistry, temperature, reactivity, water/cement ratio, presence of
cement additives, etc.
FIGS. 5A to 5E illustrate different hydration curve scenarios. The
hydration behavior of a cement having a balanced sulfate content is
shown in FIG. 5C. The solid line represents the heat flow, or rate
of heat released by the cement system, over time. The dotted line
represents the second derivative of the heat flow. In this set of
figures (FIGS. 5A-5E), the heat flow is normalized and centered
(i.e. the mean of the signal is subtracted from the signal and the
result is divided by the standard deviation of the signal). In FIG.
5C, both the peak exothermic value corresponding to maximum
C.sub.3S dissolution reaction rate (which is noted by the "X"
symbol, appearing at the peak) and the visible "onset" of the
renewed C.sub.3A dissolution reaction (which is represented by the
"I" symbol appearing in the valley between peaks) are shown. Those
skilled in the art will appreciate that the hydration curves (shown
as solid lines) in FIGS. 5A-5E are summations or composites of
separate reaction curves each having peaks (corresponding to
primarily silicate and aluminate dissolution and precipitation
reactions in the cement during hydration). Thus, the actual onset,
or initiation of, the renewed C.sub.3A dissolution reaction that
happens when there is no more available sulfate in hydrating
cement, overlaps with the C.sub.3S reaction and vice versa. Thus,
in line with typical methods in the industry (including e.g., ASTM
C563-17), the present inventors focus on the visible onset from the
calorimetry curve. Further analysis, such as taking first and
second derivatives of the heat flow can help identify a
reproducible renewed C.sub.3A onset, as one can see a local maximum
in the second derivative in FIG. 5C corresponding to the onset of
the renewed C.sub.3A dissolution (noted by the "|"). In FIG. 5C,
the aluminate (C.sub.3A) onset ("|") occurs after the maximum rate
of heat released due to the C.sub.3S ("X"). It should be noted that
separating the summations or composites of the reaction curves
(e.g. the silicate reaction from the aluminate reaction) of the
hydration curve is very difficult, and often requires other very
sophisticated test methods to be run in parallel (see e.g.
"Interaction of silicate and aluminate reaction in a synthetic
cement system: Implications and the process of alite hydration," in
Cement and Concrete Research 93 (2017) pp. 32-44 by Bergold et
al.)
The difference between the times at which these two events
described above occur is referred in this present invention as the
Delta, .DELTA. (i.e. time at C.sub.3A onset minus time at maximum
C.sub.3S rate of heat release). In these cases where the system is
oversulfated, Delta (.DELTA.) will be greater than zero. In FIG.
5D, the Delta is larger, and the shoulder or onset of the renewed
C.sub.3A dissolution is less pronounced. However, the local maximum
of the second derivative can still clearly identify the onset. In
FIG. 5E, the shoulder is barely perceivable, and the local maximum
of the second derivative may be considered on the same order of
magnitude as the noise in the system. Although the time at maximum
C.sub.3S rate of heat release is clearly defined, in this case, a
system required to identify a Delta value may be programmed to
assign an extreme oversulfated indicator instead of an actual Delta
since the onset of the renewed C.sub.3A reaction is not clearly
identifiable (through means such as a determining the local maximum
of the second derivative). If the Delta is adjusted towards zero
(becoming smaller), eventually, a local maximum of the second
derivative will become clear, and the system can switch over to
predict a numerical value for Delta when the second derivative
clearly provides an indication of the renewed C.sub.3A onset. It
should also be noted how clearly the maximum C.sub.3S rate of heat
release is identified in over-sulfated systems (e.g. FIGS.
5C-5E).
In some cases, when the cement does not have sufficient sulfate for
controlling the renewed C.sub.3A reaction, the C.sub.3A dissolution
will complete before the peak of the silicate reaction. In this
case, there is no renewed reaction after the peak in the C.sub.3S
rate of reaction leading to a visible onset. However, there is a
visible shoulder that is due to the completion of the C.sub.3A
reaction. This shoulder will appear earlier in time with respect to
the C.sub.3S peak. This is illustrated in FIGS. 5B and 5A. In FIG.
5B, again, the maximum C.sub.3S rate of heat release is designated
at "X", while the shoulder is designated at "|". Strictly speaking,
the shoulder here is actually the visible change in curvature of
the curve corresponding to the completion of the aluminate
reaction, that is, the point at which the dissolution of the
C.sub.3A is substantially complete. After the completion of the
aluminate reaction, the heat flow is primarily due to the silicate
reaction. For simplicity, this feature (shoulder or visible change
in curvature) is still called the onset. As was shown in FIGS. 5C
and 5D, the onset is still clearly indicated by a local maximum in
the second derivative in FIG. 5B. In a consistent manner, the Delta
(.DELTA.) is determined by subtraction the time of maximum C.sub.3S
rate of heat release from the "onset". In these cases, the Delta
will be less than zero. If the system is mildly undersulfated, the
C.sub.3A is allowed to react in an uncontrolled manner, and begins
to hinder the C.sub.3S reaction (see FIG. 5A). In this case, the
global peak corresponds to a combined heat signal from both the
C.sub.3S and C.sub.3A. Thus, this global peak is not strictly the
C.sub.3S peak, and cannot be used as such. In this case, the
C.sub.3S peak can be estimated from proper sulfated systems with
nominally the same clinker. An undersulfated system is demonstrated
in FIG. 5A, where there is no clear shoulder or sharp peak in the
curve, and the second derivative shows no major local maximum.
Similar to the extreme over-sulfated condition, a system required
to return a Delta value may be programmed to recognize these
conditions and assign an undersulfated indicator instead of a
numerical Delta value. As the Delta is adjusted towards zero
(becomes larger), eventually, a local maximum of the second
derivative will become clear, and the system can switch over to
predict a numerical value for Delta when the second derivative
clearly provides an indication of the "onset".
The preceding paragraphs demonstrate one method to determine the
Delta values. Other methods exist such as those outlined in ASTM
C563-17, ASTM C1679-17, and in "Moving towards Automation"
published in World Cement (July 2017).
In FIG. 6A, 1 day compressive strength (measured in megapascals) is
measured for three different cements (A, B and C) as a function of
cumulative exothermic (heat output) over a 24-hour period
(Joules/gram of cement). Furthermore, a square around the data
points indicates the maximum strength for the given cement.
Although within a given cement, the heat output correlates
generally with the strength, the maximum strength occurs at a
different heat output for each cement.
However, as shown in FIG. 6B, when one day compressive strength
values (megapascals) were measured for three different cements and
plotted on a graph as a function of Delta (.DELTA.), what appears
to be a cogent pattern can be observed. In other words, the maximum
strength of a cement is attained when its .DELTA. value is in the
range of (-)1 hours to (+)4 hours; more preferably, when its
.DELTA. value is (-)0 hours to (+)3 hours; and, most preferably,
when its .DELTA. value is 0.5-2.5 hours.
Based on the above discussion, a more complete and precise
definition of the term Delta can be presented. A used herein, the
term "Delta" (.DELTA.) refers to the time lapse (e.g., hours)
between the exothermic peak corresponding to the silicate reaction
(C.sub.3S) and the visible onset of the exothermic peak which
corresponds to (or approximates occurrence of) the renewed
tricalcium aluminate reaction (C.sub.3A) during hydration of the
cement for systems that are oversulfated. In systems that are
undersulfated, "Delta" (.DELTA.) refers to the time lapse (e.g.,
hours) between the exothermic peak corresponding to the silicate
reaction (C.sub.3S) and the visible change in curvature
corresponding to the completion of the tricalcium aluminate
reaction (C.sub.3A).
Although the relationship discussed above between strength and
sulfate content was first explained by Lerch in 1946 ("The
influence of gypsum on the hydration and properties of Portland
cement pastes", Proceedings, Vol. 46 of the American Society of
Testing Materials), and is reflected in various standards including
ASTM C563-17, the complexity of the cement production process
severely limits the ability to control strength consistently. More
recent means have been proposed to use the Delta as an ongoing
quality control method, whereby the Delta found in calorimetry
curves at the sulfate level giving the maximum heat output over the
desired control period, for instance one day, three days etc., is
used as a control target. However, as it takes a significant time,
typically 8-24 hours for the hydration to progress to the point the
Delta can be calculated, this must result at best in sulfate being
adjusted to the conditions of 8-12 hours ago, not to the present
time. Furthermore, this optimum Delta may have been established
months ago, on potentially very different clinker, so the logic
that controlling to a past optimum Delta is limiting the utility of
such an approach. In the present invention, the Delta is determined
continuously, and the optimum Delta target can be continuously
refined by inclusion of recent test data in the model and even
predicted in real-time. The present inventors therefore believe
that frequent and continual monitoring of both the Delta and
optimum Delta can best be performed using infrared radiation
(IR).
As used herein, the term "infrared" refers to light or radiation
energy having wavelength(s) in the range of 750 nanometers (nm) to
1000 micrometer (.mu.m). The infrared (IR) radiation is commonly
divided into three regions: the near IR (0.8-2.5 .mu.m), mid IR
(2.5-25 .mu.m) and far IR (25-1000 .mu.m) wavelengths. Infrared
(IR) waves interact with a molecule, based upon vibrational changes
of the atoms within the molecule. A portion of the radiation is
absorbed, while the other portion is reflected radiation which can
be sensed using an IR sensor and can be monitored. The IR spectrum
reflected is a unique property of each molecule. The IR spectrum
can serve as fingerprint to identify the presence and/or
concentration of a molecule in a compound or material sample,
including mixtures of ground particles as in the present invention.
It is believed by the present inventors that, while mid IR has been
used for organic compounds, the use of near IR ("NIR"), having
higher frequency, can provide a greater resolution of
information.
The use of IR sensors for assessing the content or quality of
cement, clinker, and other powder materials, and for changing
processing conditions, based on the spectral reflection is
well-known. For example, in GB 2 111 193 .DELTA. (1983), Ironmonger
taught that IR could be used for irradiating a bed of clinker
transported on a conveyor belt, and, based on the color reflection,
could be used for determining whether the material had sufficient
calcium oxide content. By using a comparator circuit to compare
signal output with a threshold value, Ironmonger taught that the
output stage could be used essentially to provide a control signal
whereby corrective action would automatically be taken if the
detection signal were to rise above the threshold. See e.g., GB 2
111 193 A at page 2, lines 54-59. As another example, in US Publ.
No. 2003/0015663, Mikula et al. explained that certain peaks of
intensity of reflected infrared (NIR) correlated with degrees of
oxidation in oil sand ore; and they proposed on-line monitoring as
a means for determining the degree of oxidation so that the
information could be used to adjust processing conditions
automatically (See e.g., US 2003/015663 at paragraphs 0002-0009).
In Publ. No. 2004/0021077 A1, Ambuel commented that NIR analyzers
were used for decades to measure constituents in pharmaceutical,
refining, chemical manufacturing, and medical diagnostic fields,
and thus models could be used based on the spectra to predict
individual components and content. In his U.S. Pat. Nos. 7,310,581;
7,663,108; and 7,924,414; Mound confirmed that IR spectroscopic
analysis could be used for analyzing bulk materials, and in U.S.
Pat. No. 7,924,414 he specifically noted that IR analyzers could be
used for analyzing "the mixture of clinker and gypsum transported
to a mill (160), and the cement composition transported to silos
for storage (175)" (See U.S. Pat. No. 7,024,414 at column 11, lines
49-56).
Data based on near infrared red (NIR), for example, has been
successfully correlated with concentrations of various chemical
species, and this has been used is the study of cement systems. For
example, in U.S. Pat. No. 5,475,220, correlations between cement
phases (e.g. C.sub.3S, C.sub.3A) and NIR spectra are demonstrated.
Similar results can be found in U.S. Pat. No. 8,887,806. These
types of correlations are practiced today (see e.g.,
http://www.spectraflow-analytics.com/products.html). Although
chemical species are predicted today, correlations to performance
characteristics such as strength and Delta (.DELTA.) have not been
discovered until the present invention. Furthermore, prior art such
as U.S. Pat. No. 7,924,414 focus on the raw materials entering the
kiln, and subsequent process changes concerning the kiln (see e.g.,
Column 10, Line 66 through Column 11, Line 16).
Hence, the present inventors believe that by using a suitable
energy source (e.g., infrared emitter) to irradiate ground
particles of cement as they exit the grinding mill, and measuring
the reflected IR radiation using an IR sensor, one may obtain
information about the sulfate type and level in the ground
particles. One can also obtain predicted values for actual
performance properties corresponding to cement/sulfate particles
having the same or similar IR data profile. For example, the
reflected IR data collected by the sensor can be compared using a
computer processor which is programmed to access database memory
wherein IR data of previous ground clinker and calcium sulfate
materials are stored along with (known or assigned) properties of
the materials.
The invention is illustrated by the following enumerated example
embodiments, including various exemplary aspects within the
enumerated example embodiments. The following paragraphs describe a
method for manufacturing cement; and, although "method" is
ostensibly the term used for framing various process steps, it
should be understood that the example embodiments, and various
aspect descriptions, which follow also describe a "system" in that
a computer processor electrically or electronically communicative
with various sensors can be configured or programmed to perform the
variously described steps, as follows.
In a first example embodiment, the present invention provides a
method for manufacturing cement, comprising:
(A) introducing, into a grinding mill, raw materials comprising
clinker, a source of sulfate chosen from gypsum, plaster, calcium
anhydrite, or a mixture thereof, and optionally one or more
supplemental cementitious materials; grinding the raw materials,
optionally with one or more cement additives, and optionally with
water, to produce a ground blend of particles comprising ground
clinker and calcium sulfate; and separating the ground blend of
particles within a classifier whereby a first portion of the
particles or the finished cement are sent to a silo or other
receptacle for containing the finished cement and whereby a second
portion of the particles is recirculated into the grinding mill for
further grinding;
(B) providing at least at least one sensor system chosen from
infrared sensor system, laser diffraction sensor system, or both,
and detecting emanation, reflectance, transmittance, or absorption
of energy by or through the ground blend of particles or finished
cement provided in step (A), and generating output signals
corresponding to the detected energy;
(C) comparing output signals generated in step (B) to data stored
in processor-accessible memory, the stored data comprising output
signal values previously obtained from sensors measuring the
emanation, reflectance, transmittance, or absorption of energy in
the infrared spectrum, laser diffraction spectrum, or in both the
infrared and laser diffraction spectrums (the stored data being
correlated with a physical or chemical property of the
corresponding finished cement, hydrated cement or cementitious
product made with the cement, e.g., (i) strength test data, (ii)
exothermic data; (iii) set initiation data; (iv) slump data; (v)
dimensional stability data; (vi) air content data; (vii)
prehydration level data; (viii) reduction or burn conditions data;
(ix) cement particle size distribution data; or (x) a combination
thereof); and
(D) in response to the comparison in step (C), adjusting (i)
amount, form or both amount and form of calcium sulfate introduced
into the grinding mill in step (A); (ii) classifier settings,
thereby to change relative amounts of ground particles being sent
to the silo and being recirculated back into the grinding mill;
(iii) amount, type, or both amount and type of cement additives
introduced into the grinding mill; (iv) amount of water being
introduced into the grinding mill; (v) the amount of air provided
by adjusting power or speed of a fan or blower connected to
ventilate the mill; (vi) amount or type of supplemental
cementitious material introduced into the grinding mill; (vii)
cement cooler setting, thereby to change the temperature of the
finished cement or (viii) combination of any of the foregoing
(e.g., in order to modify a physical or chemical property of the
finished cement).
In a first aspect of the first example embodiment, step (B)
comprises irradiating the ground blend of particles or finished
cement obtained from step (A) using an infrared and/or laser
radiation source. More preferably, the radiation comprises
electromagnetic radiation having wavelengths in the range of 300 to
1,000,000 nanometers (nm). In preferred example embodiments, the
sensors are part of an integrated system wherein an emitter or
radiation unit is combined with a sensor.
In a second aspect of the first example embodiment, the grinding
mill may be chosen from a ball mill or roller mill, such as a
vertical roller mill. The term "roller mill" includes vertical
roller mills ("VRMs") as well as horizontal roller mills (e.g.,
Horomill.RTM. brand horizontal roller mills), as well as mills that
crush particles into finer size through nipped opposed rollers.
VRMs have rollers which are pneumatically controlled to rotate in
vertical direction upon a circular rotating table, and have a
classifier that is integrated into or part of the same housing
which contains the rollers and revolving table; and particles are
fed into the center of table and move towards the outer
circumference of the revolving table and crushed under the path of
the rollers which are actuated by pneumatically assisted armatures.
In VRMs, for example, at least one IR sensor is preferably located
at the exit of particles from the housing which encloses the roller
and classifier mechanisms, or, alternatively, along the pathway or
conduit to the storage silo.
In a third aspect of the first example embodiment, the method
comprises using the at least one sensor system to detect the
infrared (IR) (e.g., energy having wavelengths in the range of 700
to 1,000,000 nanometers (nm) based upon IR reflected by,
transmitted through, or absorbed by the ground blend of particles
or finished cement. (Note: 700 to 1,000,000 nm wavelength
corresponds to frequencies of 430 THz to 300 GHz). The at least one
sensor system will preferably have ability to detect infrared
radiation wavelengths in the range of 700 nm to 8 .mu.m (430 THz to
37 THz); more preferably, in the range of 700 nm to 3 .mu.m (430
THz to 100 THz); and, most preferably, 700 nm to 1400 nm (430 THz
to 214 THz). NIR (Near Infrared Radiation) is typically 750-1400 nm
(400-214 THz). SWIR (Short Wavelength IR) is typically considered
to be in the range of 1400-3000 nm (214-100 THz). MWIR
(Mid-Wavelength IR) is typically considered to be in the range of
3-8 .mu.m (100-37 THz). LWIR (Long-Wavelength IR) is typically
considered to be in the range of 8-15 .mu.m (37-20 THz). FIR (Far
IR) is typically 15-1000 .mu.m (20-0.3 THz). ISO 20473 specifies
that NIR encompasses the range of 0.78-3 .mu.m, MIR (mid-infrared)
encompasses the range of 3-50 .mu.m, and FIR (far-infrared)
encompasses the range of 50-1000 .mu.m.
More preferably, the at least one sensor system provides output
signals corresponding to the reflectance of energy by or through
the ground blend of particles or finished cement. Using a sensor to
measure reflectance (i.e., scattered reflection from the bed of
particles) of energy from the IR source is preferred to measuring
transmitted or absorbed energy. In still further exemplary
embodiments, the sensor system may provide output signals
corresponding to discrete wavelength ranges, regions, or specified
spectra. One may employ two or more IR sensors, each dedicated to a
region within the IR range.
In a fourth aspect of the first example embodiment, the invention
provides a method involving use of the at least one sensor system
which comprises a source of radiation wavelengths in the range of
300-700 nm emitted by a laser, and obtaining data based upon
scattering of this radiation by and/or through the irradiated
ground blend of particles or finished cement. Two types of lasers
are commonly used for particle size analysis. First are red lasers,
which typically are generated by HeNe lasers, producing red light
at 632.8 nm. Laser diodes are also available, which use GaInP or
AlGaInP quantum wells. The second type of lasers are blue lasers
for wavelength detection in the range of 360 nm to 480 nm.
Helium-cadmium gas lasers produce blue light at 441.6 nm, while
argon-ion lasers can produce blue light having wavelengths in the
range of 458 nm to 488 nm. Diode lasers (445 nm) are becoming more
popular due to price. Semiconductor lasers, such as gallium nitride
(GaN) can produce blue light as well. Many advances are occurring
this area with new Thulium-doped and praseodymium-doped
up-conversion lasers.
In a second example embodiment, which may be based upon the first
example embodiment above, the invention provides a method wherein
steps (A) through (D) are performed and repeated on at least a
monthly basis or at shorter time intervals.
In other words, in a first aspect of this second example
embodiment, the method more preferably involves steps (A) through
(D) being performed and repeated on at least a weekly, daily,
once-per-shift, or even hourly basis. Most preferably, the interval
is every 15 minutes, and even smaller intervals such as every 2-5
minutes.
In a third example embodiment, which may be based upon any of the
first through second example embodiments above, the invention
provides a method wherein steps (A) through (D) are performed and
repeated for successive 100,000 metric tons (MT) of cement clinker
being ground in the grinding mill. More preferably, the steps can
be repeated at more frequent intervals (e.g. 10,000, 1,000, or even
smaller intervals).
In other words, in a first aspect of this third example embodiment,
the method involves steps (A) through (D) being performed and
repeated for successive 10,000 metric tons (MT), more preferably
every 1,000 MT, even more preferably for successive 100 MT, and
most preferably for successive 10 MT of cement produced.
In a fourth example embodiment, which may be based upon any of the
first through third example embodiments above, the invention
provides a method wherein steps (A) through (D) are performed and
repeated upon a detected change in the cement production process.
For example, the detected change can involve a fuel change, a
material input change (e.g., composition of clinker, limestone,
cement additives), water spray level or spray rate, temperature,
internal or external air temperature, etc.).
In a first aspect of the fourth example embodiment, steps (A)
through (D) are performed and repeated upon a change in the
production process corresponds to a change in the kiln fuel feed
rate or fuel type. It is known that the type of fuel used to heat
the kiln can have a major impact on the aluminate-sulfate balance
of the clinker. Examples of fuel types are coal, petcoke, oil,
natural gas, as well as alternative fuels such as municipal waste,
industrial waste (e.g. waste oil, animal feed, used carpets, used
tires, etc.). Each of these fuels have different sulfur contents.
Furthermore, within a given fuel, for example, for municipal waste,
the sulfur can vary over time. Therefore, changes in fuel can cause
issues for the cement producer as the resulting changes in the
clinker need to be accounted for. Automatically detecting the
change in the sulfate-aluminate balance (and making the necessary
adjustments) not only enables a more consistent product through the
fuel type change, but also can enable more fuel changes without
performance issues. In particular, the switching from a high sulfur
containing fuel to a lower sulfur containing fuel can have an
especially dangerous impact on sulfate-aluminate balance, as it can
cause formation of more highly reactive orthorhombic C.sub.3A.
Using the present invention, these situations can be overcome to
balance the sulfate correctly for each fuel. This can be very
beneficial for the environment as highly variable fuel sources such
as waste (e.g. municipal waste), and can be used. The present
invention thus allows for more variable fuel sources to be
used.
Moreover, the NIR system can be used to determine variations in
pertinent cement chemical components (e.g. sulfates, calcium
aluminate form), and this can help to select the optimum type and
proportions of different fuels to maintain a balanced
sulfate-aluminate system. For instance if high variation in
orthorhombic to cubic C.sub.3A ratio is detected by the NIR system,
waste fuel streams can be adjusted to maintain consistent alkali to
sulfate balance. Further, if environmental constraints dictate fuel
blend changes on such a basis that the proper alkali sulfate
balance is difficult to achieve, and the NIR system detects such
issues, then compensating kiln feed composition changes can be
made. As another example, if fuels used cannot supply enough sulfur
to balance the alkali levels inherent in the raw materials, gypsum
may be added to the raw feed to supply the needed available
sulfate. These possibilities have previously been understood, but
the NIR system's ability to continuously monitor composition is
essential in enabling the determination of the level of variance
and thus the relative importance of taking such steps. As
orthorhombic C.sub.3A formation is also influenced by reducing
conditions in the kiln, variation in the ratio absent
sulfate-alkali balance changes in the kiln feed and fuel can be
indicative of burning issues, which can then be addressed.
In a second aspect of the fourth example embodiment, the invention
provides a method wherein steps (A) through (D) of the first
example embodiment are performed and repeated when a compositional
or chemical change in the raw materials, the raw meal, clinker, the
finished cement or combination thereof, exceeds a predefined
threshold. In particular, if C.sub.3A orthorhombic content within
the clinker (as measured or estimated from, for example by XRD,
XRF, etc.) exceeds a predefined threshold, steps (A) through (D)
can be executed.
In a third aspect of the fourth example embodiment, the invention
provides a method wherein steps (A) through (D) of the first
example embodiment are performed and repeated when a change in the
cement fineness exceeds a predefined threshold, such as a maximum
deviation value (fineness target or range). This fineness
characteristic can be measured offline (e.g. with a manual Blaine
measurement) or online (e.g. with a particle size analyzer).
In a fourth aspect of the fourth example embodiment, the invention
provides a method wherein steps (A) through (D) of the first
example embodiment are performed and repeated when a change in a
kiln process, a mill process or a both occurs. For example, if the
flame length changes within the kiln, steps (A) through (D) can be
executed. As another example, if the water spray rate within the
mill is changed, steps (A) through (D) can be executed.
In a fifth example embodiment, which may be based upon any of the
first through fourth example embodiments above, the processor is
programmed to adjust the sulfate entering the mill in terms of
calcium sulfate type, feed rate, or both type and feed rate. For
example, this may be accomplished by adjusting feed rate of a
calcium sulfate source into the mill or the ratio between forms of
sulfate. As another example, during introduction of sulfate
materials into the mill, one may add a combination of gypsum and
anhydrite into the mill; and, once these are in the mill, one may
adjust the temperature and moisture within the mill to control the
dehydration of gypsum to plaster.
In a first aspect of the fifth example embodiment, the source of
calcium sulfate introduced into the mill in step (A), whether in
the form of gypsum, plaster, or anhydrite, can include synthetic
versions (e.g., synthetic gypsum), phosphogypsum, as well as
natural forms (e.g., natural anhydrites). Sulfates can include
alkali or alkaline earth sulfates (e.g., calcium sulfate, sodium
sulfate, potassium sulfate).
In a second aspect of the fifth example embodiment, the ratio
between different forms of sulfate entering the mill is determined
by using a sensor that monitors the sulfate source entering the
mill. For example, an NIR sensor can be programmed to detect the
relative amounts of gypsum and anhydrite (as plaster is rarely
added into the mill, but appears as the gypsum is dehydrated once
inside the mill) within the sulfate source being introduced into
the mill. The processor can be programmed to use this information
to adjust the total sulfate feed rate, adjust individual rates of
gypsum and/or adjust mill processes that can control the ratios
between the different sulfate forms after being introduced into the
mill (including the gypsum to plaster ratio).
Both the amount and form of sulfate can affect characteristics of a
cement, such as its strength and Delta. Thus, in a third aspect of
the fifth example embodiment, the exemplary method further
comprises storing data regarding total and relative amounts of the
different sulfate forms entering the mill, and this can be
performed during steps (A) through (C), and the data can be stored
into processor-accessible memory (e.g., for use as later reference
values). By combining the sulfate information as well as
performance predictions generated from step (C), relationships
between the sulfate adjustments and performance characteristics can
be developed and used to make more efficient adjustments to the
cement production process.
In a sixth example embodiment, which may be based upon any of the
first through fifth example embodiments above, the processor can be
programmed to adjust supplementary cementitious materials (SCM)
entering the mill (e.g., being introduced into the mill at step
(A)) in terms of type or feed rate, or both type and feed rate.
This may be done for example by adjusting feed rate of an SCM
source into the mill, the ratio different types of SCM introduced
into the mill, or the respective feed rate of different SCM sources
into the mill. For example, if a prediction based on the NIR, LD, T
and/or M/RH sensors indicate that the strength (e.g. 1, 28 day) of
the finished cement is 10% higher than a pre-defined strength
target, the amount of fly ash can be adjusted until the predicted
strength of the finished cement (including the adjusted proportion
of fly ash) is reduced to the target. A similar approach can be
taken if the predicted strength is lower than the target.
In a first aspect of the sixth example embodiment, the source of
supplementary cementitious materials (SCMs) introduced into the
mill in step (A) is chosen from limestone, fly ash, granulated
blast furnace slag, clay, calcined clay, natural pozzolan, or a
mixture thereof.
In a second aspect of the sixth example embodiment, the chemical
composition of SCMs entering the mill can be monitored using one or
more sensors to measure SCM entering the mill. For example, an NIR
sensor can be programmed to detect the additional source of
aluminates within the SCMs that must be accounted for in order to
accurately adjust the sulfate-aluminate balance, which can affect
the strength of the cement. SCMs may also have a more negative
impact on early strength development due to higher amorphous
contents and thus deserve monitoring and consideration in the
comparison and adjustment steps.
In a third aspect of the sixth example embodiment, the exemplary
method further comprises storing information regarding composition
of the SCM in a processor-accessible database during performance of
steps (A) through (C), and the data can be stored into
processor-accessible memory (e.g., for use as later reference
values). By combining the composition characteristic (e.g. C.sub.3A
content, amorphous content) information as well as performance
predictions generated from step (C) of the first example
embodiment, and relationships between the SCM adjustments and
performance characteristics can be developed and used to make more
efficient adjustments to the cement production process.
In a seventh example embodiment, which may be based upon any of the
first through sixth example embodiments above, the processor is
programmed to adjust the introduction of chemical additives into
the grinding mill in terms of type, formulation, amounts, dosage
rate, or a combination thereof. For example, the dosage rate of a
particular chemical or group of chemicals may be adjusted. The
relative amounts of chemicals used in a formulation may be
adjusted. As a further example, the processor can be programmed to
adjust the rate by which specific chemical additives are introduced
into the grinding mill.
The cement additive can be a conventional grinding enhancement
additive, a strength enhancing additive, or other agent, or
combination thereof, that modifies one or more properties of the
cement during grinding, of the cement during hydration, or of the
cement material after it is hardened into concrete, mortar,
masonry, or a structure. The cement additive amount can be adjusted
based on a strength prediction or other performance parameters,
such as Delta, total heat released over a specified period of time
(e.g. 24 hours), set time, slump, dimensional stability,
prehydration level, etc. For example, if a prediction based on the
NIR, LD, T and/or M/RH sensors indicates that the strength of the
finished cement is 10% lower than a pre-defined target strength for
a given age (e.g. 1 day or 28 days), the amount of a strength
enhancing cement additive can be adjusted until the predicted
strength of the finished cement (including adjusting proportion of
cement additive) is increased to the target. If the predicted
strength is higher than the target, the classifier setting can be
adjusted to decrease the Blaine specific surface area in order to
reduce the mill energy consumption, thus providing an energy and
cost savings. Adjustment of chemical additive dosage can also cause
a change in temperature due to the change in grinding efficiency.
Using a combination of adjustments to both the sulfate feed and
mill conditions, a wide variety of absolute amounts of
gypsum/plaster/anhydrite can be achieved.
In a first aspect of this seventh example embodiment, the cement
additive may be a conventional alkanolamine or acetic acid
(including any salt or derivative thereof. For example, this may
include triethanolamine ("TEA"), acetic acid, triisopropanolamine
("TIPA"), diethanolisopropanolamine ("DEIPA"),
ethanoldipropanol-amine ("EDIPA"), tetrahydroxyethylethylene
diamine ("THEED"), methyl-diethanolamine ("MDEA"), ethanol
diglycine ("EDG"), a glycol, a glycerol, and mixtures thereof.
Other conventional additives may be employed as desired by those
skilled in the art.
In a second aspect of this seventh example embodiment, the cement
additive may be chosen from the group of set accelerators and
strength enhancers comprised of chloride, bromide, thiocyanate,
iodide, perchlorate, formate, thiosulfate, nitrate and nitrite
alkali or earth alkali salts (such as sodium sulfate), and mixtures
thereof.
In a third aspect of this seventh example embodiment, the cement
additive may be chosen from the group of set retarders comprised of
gluconate salt, gluconic acid, molasses, sucrose, or corn syrup, or
mixtures thereof.
In a fourth aspect In a third aspect of this seventh example
embodiment, the cement additive may be chosen from defoamers
comprising of (i) ethoxylated, propoxylated fatty alcohol or
alkylphenol, (ii) polyalkoxylated polyalkylene polyamine, or (iii)
a mixture thereof.
In a fifth aspect of this seventh example embodiment, the cement
additive may be a combination of the above cement additives that
provides performance enhancement to the ground cement. For example,
organic acid chemicals such as tartaric or citric acid may be added
to control the C.sub.3A side of the sulfate balance to complement a
sulfate adjustment if needed (e.g. in situations where no more
sulfate can be added because of limitations imparted by ASTM
C1038/C1038M-14b).
In a sixth aspect of this seventh example embodiment at least one
compositional or categorical characteristic of the chemical
additive is stored in a processor-accessible database during
performance of steps (A) through (C), and the data can be stored
into processor-accessible memory (e.g., for use as later reference
values). Compositional characteristics may include, for example,
the relative amounts of certain chemicals within the chemical
additive (e.g. amine, defoamer, etc.). A categorical characteristic
can simply be the identification label for the given additive. By
combining this information as well as performance predictions
generated from step (C), relationships between the adjustments and
performance characteristics can be developed and used to make more
efficient adjustments to the cement production process. In other
words, the formulation of the additive can be adjusted in real time
based on how efficient the additive formulation is in adjusting one
or more performance characteristics.
In an eighth example embodiment, which may be based upon any of the
first through seventh example embodiments above, the processor is
programmed to adjust a kiln process, a mill process or both.
In a first aspect of this eighth example embodiment, the processor
is programmed to adjust the operation of the classifier that is
used for removing sufficiently fine particles to send them to the
storage silo and to recirculate coarser particles back into the
mill. For example, the classifier can be adjusted to select out
finer or coarser particles. The classifier can be adjusted a number
of ways to change the particle size distribution and/or specific
surface area of the finished cement, including air speed within the
classifier, the rotational speed of distribution plates, vane
settings, loading rates, and other factors. Many performance
aspects of cement are affected by the particle size distribution
and/or specific surface area, including strength, set time,
workability, etc. By performing adjustments to the classifier,
these performance characteristics can be adjusted. The classifier
can also be adjusted in response to other changes in the mill
process, such as to the introduction of a grinding aid. Because
grinding aids can increase the efficiency of the grinding and
classification process, the classifier can be adjusted to take into
account the efficiencies imparted by the grinding aids to realize
potential energy and cost savings.
In a second aspect of this eighth example embodiment, the processor
can be programmed to adjust the operation of the water spray rate
within the mill. One way to adjust the sulfate source is to control
the temperature and humidity within the mill and thus the
dehydration of gypsum to plaster (and furthermore to anhydrite in
some cases), i.e. the ratio between the sulfate forms
(gypsum/plaster/anhydrite). Temperature and humidity can be
adjusted through the control of the mill water and temperature
systems. Using predictive models, or real-time feedback from
sensors (e.g. temperature, moisture or relative humidity sensors),
the processor can be programmed to adjust water spray rate to
adjust the temperature and humidity and thus the rate or amount
dehydration of gypsum to plaster. Minimizing water spray helps to
avoid or to minimize prehydration of the cement.
In a third aspect of this eighth example embodiment, the processor
can be programmed to adjust the amount of air provided to ventilate
the mill by adjusting the power or speed of a fan or blower
connected to the mill. In addition to the water spray, the fan
pulling air through the mill can also control the temperature (and
thus the forms of sulfate). Again, a predictive model or real-time
feedback from sensors can be used to determine deviations from
pre-defined targets and thus what adjustments need to be made to
incur a change of the gypsum/plaster/anhydrite forms.
In a fourth aspect of this eighth example embodiment at least one
process parameter of the kiln or mill is stored in a
processor-accessible database during performance of steps (A)
through (C), and the data can be stored into processor-accessible
memory (e.g., for use as later reference values). Process
parameters may comprise, for example, the water spray rate, the air
speed, a flame size, a fuel rate, an elevator bucket speed, etc. By
combining this information as well as performance predictions
generated from step (C), relationships between the process
adjustments and performance characteristics can be developed and
used to make more efficient adjustments to the cement production
process.
The processor for purposes of step (D) can be programmed to perform
adjustments to achieve a variety of changes to the cement
production system to improve the quality of the cement. For
example, the sulfate amount, the SCM blend, and any cement
additive(s) can be optimized, in terms of amounts and in real time,
to produce a target or maximum strength at 1 day (or other "ages"
such as 28 days). As another example, the amount of water spray,
air flow, and temperature can also be optimized for maximizing
strength. Any of these factors or combination of these factors can
alternatively be optimized for a target set time, or for
compatibility with a particular concrete admixture. Another
possibility is optimizing the sulfate-aluminate balance for a given
climate (e.g. hot climates require more sulfate). Aside from
optimization, characteristics such as strength can be optimized for
consistency. That is to say, for example, the sulfate may be
optimized for the given clinker, but the strength can be reduced
(or increased) to match a target strength by, for example,
adjusting the fineness of the cement (which depends on a control
loop involving a particle size prediction from, for example a laser
diffraction sensor system, or NIR sensor system) and/or by
adjusting the type or amount of cement additive.
The choice of which adjustment(s) to make can be prioritized based
on several factors. Some cement plants may be able to adjust only
some of the processes described in (i) to (vii) of step (C) of the
first example embodiment above. For example, blended cements
(clinker with SCMs) are not common in the USA, and require
additional feed systems. However, in Europe, blended cements are
typical. The adjustments may also be prioritized based on their
relative effect upon performance. For example, as fineness has a
major impact on the strength of the cement (especially at early
ages), it may be one of the first processes to adjust (such as by
adjusting the separator settings and/or adjusting the dosage of the
grinding aid). However, if prioritizing is based on manufacturing
cost, it may be more preferred to grind coarser particles and
instead add or adjust strength enhancing cement additives, decrease
the amount of SCMs or adjust the sulfate balance. In another
scenario, the CO.sub.2 emissions may be a priority, and in this
case, the amount of SCMs may be increased, which may require
adjustments to the fineness, cement additive content or sulfate
balance. Prioritization also depends on the sensor systems
employed. Using an NIR sensor system with a laser diffraction
sensor system may allow the cement plant to measure and manage the
sulfate balance, and at the same time maintain the strength at a
constant value by measuring and managing the fineness as well as
adding cement additives. The choice of adjustments can also depend
on balancing several different performance factors. For example, a
particular sulfate level may be ideal for achieving a certain
target strength, but not so favorable for achieving an acceptable
setting behavior, or slump, slump retention as well as admixture
response. The present invention thus makes it now possible to have
flexibility to manage all of these different scenarios.
In a ninth example embodiment, which may be based upon any of the
first through eighth example embodiments above, the method further
comprising collecting data from at least one non-IR, non-laser
sensor disposed or located within, or at the inlet or outlet of:
(i) the grinding mill, (ii) an air flow inlet, outlet, or channel
connected to grinding mill, or (iii) a kiln that produces cement
clinker material introduced into the grinding mill. The data (e.g.,
output signal, associated value) from the at least one sensor is
preferably stored and associated with data and/or associated
value(s) previously stored in processor-accessible memory, for
example, to serve as later reference values useful for step (C).
The signal output of a sensor, or a value which is associated to
the signal output, or both, may be stored into memory as a history
of the process event and can be used in step (C).
In a first aspect of the ninth example embodiment, data collected
from temperature, moisture, relative humidity sensors, or
combination thereof, is stored in with the data stored in
processor-accessible memory, where it can be used later, e.g., such
as for reference in the comparison process described in step (C).
Temperature and moisture data (which can be used to calculate
relative humidity), thus producing further data or associated
values which can be stored and used later as reference values in
step (C)) can help determine dehydration states of gypsum (to
plaster) within the mill. Also, because IR signals (i.e., NIR) are
sensitive to temperature and moisture, use of independent
temperature and moisture sensors can help to correct or to
eliminate the effects of moisture which could otherwise adversely
affect or complicate analytical predictions of cement properties
(e.g. Delta, strength) based on the IR signals.
In a second aspect of the ninth example embodiment, the method of
the invention further comprises an X-ray diffraction (XRD) sensor,
X-ray fluorescence (XRF) sensor, thermogravimetric (TGA) sensor,
particle size distribution (PSD) analyzer, prompt gamma neutron
activation (PGNAA) analysis, and further comprises obtaining data
from at least one of the afore-mentioned sensors and storing the
data in processor-accessible memory for use in later reference,
such as the previously stored data described in step (C). XRD, XRF,
TGA, PSD, or cross-belt analyzers such as a PGNAA sensor from
ThermoFisher.RTM. Scientific (of Waltham, Mass.) can be used to
provide chemical analysis on a continual basis, which can help to
confirm, improve or update calibrations for IR predictions (e.g.
Delta, strength). Such sensors can also be used to trigger any of
steps (A) through (D). For example, if the raw meal composition
changes as detected by a PGNAA sensor, steps (A) through (D) of the
first example embodiment is executed.
In a third aspect of the ninth example embodiment, exemplary
methods of the invention further comprising using an ultrasonic
sensor or other range-finder type sensor to generate data that can
be stored in processor-accessible memory (e.g., step (C)). This
information can be used, for example, to determine the distance
from an IR sensor to the measured particles as they are conveyed on
a conveyor belt or within a chute or other open channel. Using this
distance information, the NIR received signal can be corrected in
real-time for any changes in the distance from the probe to the
measured particles. As another example, a particulate concentration
sensor can be located in an air slide wherein the particles are
measured by the NIR sensor, and this particulate concentration
sensor can be used to correct in real-time for any changes in the
concentration of the measured particle within the air-slide.
Furthermore, the processor in step (C) of the first example
embodiment can be programmed to take into account additional inputs
or signals regarding the cement manufacturing system, and these can
be used to make the comparison. For example, information about the
raw feed (raw material proportions, chemical composition), kiln
processes (e.g. temperature, flame size, oxygen levels, output
volume), fuel source and chemical composition, clinker size and
chemical composition, mill processes (temperature, water spray,
ventilation, mill void filling ratio, size of steel balls used,
ball loading (which can be tied to acoustic sensor levels)). In
addition, categorical inputs such as the name of an SCM type or
additive type can be used to help indicate which data tables to use
when predicting performance. For example, strength predictions when
using a TEA-containing cement additive may be different than when
using a DEIPA-containing cement additive. The formulation name can
identify which predictive relationship to use.
In a tenth example embodiment, which may be based upon any of the
first through ninth example embodiments above, the method further
comprises providing an IR or laser sensor within an elevator
bucket, conveyor belt, air slide, or pneumatic conveying device
within or connected to the grinding mill. Sensors for measuring
reflected and/or absorbed radiation can be used on moving cement
particles, or cement particle samples which are removed from the
production stream temporarily or permanently for IR radiation
testing. Removal of a sample can be done "manually" (when desired)
or "automatically" (at programmed intervals). Hence, the sensors
used in step (B) for monitoring reflected, absorbed, and/or
transmitted IR radiation can be located within a manually operated
sampler or auto sampler.
In a first aspect of the tenth example embodiment, the method
further comprises the use of an auto sampler, preferably such that
if sufficient amount of sample can be removed from the product
stream for IR testing, additional testing can be performed to
measure strength, heat output, set time, workability, shrinkage or
expansion, air content, prehydration or clinker reduction, or burn
conditions associated with the cement.
In a second aspect of the tenth example embodiment, a combination
of sensors at various locations can be employed. One preferred
configuration involves location of a near infrared sensor (NIR), a
laser diffraction sensor (LD), a temperature sensor (T), and a
moisture or relative humidity sensor (M/RH) along or within a
conduit, conveyer belt, channel, or pipe through or along which
finished cement is conveyed from the grinding mill to a silo or
other storage container. Another preferred configuration is to have
the NIR, LD, T and M/RH sensors located along or within a conduit,
conveyer belt, channel, air slide, or pipe through which the
recirculated particles are redirected back into the grinding mill.
Still another preferred configuration is to have the T and M/RH
within the grinding mill and the NIR and LD along or within a
conduit, conveyer belt, channel, air slide or pipe through or along
which finished cement is conveyed from the grinding mill to a silo
or other storage container.
In a third aspect of the tenth example embodiment, temperature
sensors can be mounted after the grinding mill to monitor finished
cement being sent to the cement silo (or other storage for the
finished cement), including an additional temperature sensor in the
silo itself. In addition, moisture or relative humidity sensors can
also be mounted after the grinding mill to monitor the cement being
sent to the cement silo.
In a fourth aspect of the tenth example embodiment, multiple
sensors (NIR, LD, T, or M/RH) along a path (such as the path or
conduit from the mill to the storage silo; or even before, within
and after the cement cooler) or at different vertical levels within
the storage silo, may be used to enable the operator or
processor-controlled monitoring system to predict or measure the
amount of gypsum conversion to plaster due to dehydration. This
information can be used to adjust the source of calcium sulfate
such that after conveyance to the cement silo, the final product
will have the desired amount and forms of calcium sulfate. A
temperature sensor (optionally in combination with a moisture
sensor or relative humidity sensor), for example, can also be used
to predict the amount of dehydration of gypsum to plaster. In other
words, adjustments of the sulfate form and content can also be
aided by an additional feedback system where the temperature of the
finished cement as it is conveyed to the silo is monitored until
the temperature of the cement has cooled to a final temperature
(i.e. through temperature sensors installed in the silo or in
proximity of the cement cooler). This information can be useful, as
cement exiting the mill can still be at elevated temperatures (e.g.
over 100.degree. C.), and gypsum can still be dehydrating to
plaster. By measuring temperature of cement and gypsum/plaster upon
exit from the mill or classifier, and by knowing the temperature in
the silo, the amount of dehydration can be predicted. This
information can then be relayed to the processor which controls
sulfate levels, so that adjustments can be made to take into
account dehydration in the cement after it leaves the mill.
Alternatively, the cement cooler settings can be adjusted to
prevent further dehydration based on the temperature
measurements.
In a fifth aspect of the tenth example embodiment, the invention
provides a method wherein at least two energy radiation/sensor
systems are employed, one of which is based on use of infrared
sensor system having an infrared radiation emitter and infrared
radiation sensor, the second of which is based on use of a laser
diffraction sensor system having a laser emitter and radiation
sensor for detecting laser energy passing through the irradiated
finished cement. When two energy radiation/sensor systems are
employed, two independent measurements can be taken. These
independent measurements can be used to perform a variety of
different tasks, for example, one measurement can be used to
determine or improve the accuracy of the other measurement. Both
measurements can also be used in combination to help train
algorithms (e.g. regressions or machine learning sets) to predict
different performance values (e.g. strength, exothermic results
such as Delta). Where possible, the two independent measurements
can help to control different parameters such as particle size
(e.g. with the laser diffraction measurement) and sulfate balance
(e.g., with the NIR measurement as measured by the Delta
value).
In a sixth aspect of the tenth example embodiment, the invention
further comprises employing an NIR sensor to determine chemical
composition of the clinker entering the grinding mill. This signal
can be compared to signals from the ground cement, which
necessarily represents the composition of the bulk clinker, to
better refine predictive relationships. It is understood that the
signals obtained from clinker may be different compared to signals
from crushed cement as the NIR reflectance of a clinker will mostly
represent the surface. It is also understood that relative
proportions of the chemical components of the surface of clinker
may be different from the bulk of the clinker.
In an eleventh example embodiment, which may be based upon any of
the first through tenth example embodiments above, the invention
provides a method wherein, in step (C), the stored data obtained
from finished or hydrated cement, is chosen from (i) strength test
data, (ii) exothermic data; (iii) set initiation data; (iv) slump
data; (v) dimensional stability data; (vi) air content data; (vii)
prehydration data; (viii) reduction or burn conditions data; (ix)
cement fineness data; or (x) or a mixture thereof.
In a first aspect of this eleventh example embodiment, the stored
data is based on strength data and is obtained by casting a
composition comprising the irradiated finished cement and water,
with optional aggregates (either sand or gravel or both), and
allowing the composition to harden after a specified period of time
(for example, 6 hours, 1 day, 2 days, 3 days, 7 days, 28 days, 56
days, etc.). After the prescribed time has elapsed, the material
(frequently cast as a prism (including a cube) or cylinder) is
subjected to compressive load. The compressive strength (which may
be tested, for example, in accordance with ASTM C109/C109M-16a or
EN-196-1:2016,) is calculated upon failure of the specimen. These
tests are usually performed under specified environmental
conditions (e.g. temperature, humidity specifications), but can be
performed at different conditions based on where the cement will be
used by the cement producer's customers (e.g., if concrete produced
with the given cement is mostly cast in warm climates, the
specimens may be cast at temperatures elevated relative to what is
specified by e.g. ASTM C109/C109M-16a).
In second aspect of this eleventh example embodiment, the stored
data is based on calorimetric testing, whereby the heat released
from a cement paste (cement and water), mortar (cement paste with
sand), or concrete (mortar with gravel) are recorded over time.
Different types of calorimetric tests exist such as semi-adiabatic,
and isothermal (semi-adiabatic systems allow heat to leave the
system, while isothermal refers to a system where the heat is
measured at a constant temperature). Many different methods exist
to look at heat released during the hydration of cementitious
materials. For example, the total heat released over a period of
time (e.g. 24 hours) can be quantified, and has been correlated to
strength for similar cements. Heat released due to different
reactions can also be quantified both in the intensity and time at
which the reactions begin, are at their highest rate, or end.
In a third aspect of this eleventh example embodiment, the stored
data is based on set initiation data, which typically involves
initial set and final set times for a hydrated cement sample. The
set times can be determined by penetration tests (or proctor
tests), where the penetration into the material is recorded over
time, and initial and final set are determined when the penetration
meets certain prescribed values. Values such as initial set can
also be determined by other types of tests, for example using shear
wave reflection. Because liquids do not reflect shear waves, as the
material hardens (sets), the shear wave reflection increases. Set
time has also been shown to be indirectly estimated from
calorimetric testing data.
In a fourth aspect of this eleventh example embodiment, the stored
data is based on slump data. Slump data is a simplified way to
refer to rheological behavior. The rheological data may be based
upon or include data which reflects yield stress, viscosity,
thixotropy (as measured for example by a rheometer, see e.g. ICAR
rheometer), or more practical measurements such as slump (which can
be measured using the drop in height when concrete is demolded from
a truncated cone) or slump flow (which is usually measured in terms
of horizontal spread of the concrete on a steel surface). In the
cement plant environment, workability can be measured on cement
pastes by, for example, the normal consistency test (see e.g. ASTM
C187-16), or by use of flow tables with mortars (see e.g., ASTM
C230/C230M-14). Hence, for example, reflected IR data may be
correlated with slump, slump flow, or other rheology
measurements.
In a fifth aspect of this eleventh example embodiment, the stored
data is based on dimensional stability data, which involves changes
in volume over time, such as shrinkage and expansion. There exist
many standard measurements including ASTM C157/C157M-17 and ASTM
C596-09(2017), for example. Hence, for example, reflected IR data
may be correlated with such standard measurements.
In a sixth aspect of this eleventh example embodiment, a cement
additive dosage response to one or more of the stored data is
determined. The dosage response is calculated as the amount of
cement additive required to achieve a given level of performance of
a parameter such as strength at a given time (e.g. 24 hours), and
alternatively set time, shrinkage, particle size distribution
and/or specific surface area or other cement response to cement
additive may be used. Furthermore, cement additives, such as
grinding aids can also affect other properties such as the
throughput of the mill. This data, usually represented as a
response over different dosages, can be created by testing a given
performance parameter for a range of dosages. Dosage responses can
then be used to select a dosage or cement additive to be used
during the production of the cement. Alternatively, if a less than
ideal dosage or cement additive type is being used, instead of
switching the dose or cement additive, the production parameters
(e.g. sulfate form or amount) can be adjusted to improve the dosage
response. Further, if the sulfate form is less than ideal but
cannot easily be altered, the cement additive formulation can be
changed based on knowledge of interaction of the cement additives
with that sulfate form. Cement additives can, for example, include
quality improvers (which can improve strength or other properties),
grinding aids, which can improve grinding efficiency, or both.
In a seventh aspect of this eleventh example embodiment, a concrete
chemical admixture dosage response to one or more of the stored
data is determined. The dosage response is calculated as the amount
of admixture required to achieve a given performance such as
strength, set time, shrinkage reduction or other performance
response. Typical concrete admixtures include "water reducing
admixtures" (e.g., lignosulfonates, naphthalene sulfonates,
polycarboxylate dispersant polymers), retarders, and other chemical
admixtures that can affect the sulfate balance (and hence flash and
false set) in many different ways. For a cement that is close to
being under-sulfated (and hence has the risk of to flash set, or in
other cases extended set), the use of concrete admixtures may push
the cement system further towards being under-sulfated. Thus, the
cement plant may choose to optimize towards a higher Delta (i.e. a
greater amount of sulfate) in order to prevent such problems (i.e.
the Delta is optimized for the presence of the concrete admixture).
Thus, the practical target Delta may be higher than the Delta at
optimum strength, in order to accommodate known field condition
demands.
In an eighth aspect of this eleventh example embodiment, the stored
data is based on the content or volume of air entrapped or
entrained within a cementitious mixture, also known as the air
content. There exist many standard measurements including ASTM
C185-15a for mortar or ASTM C173/173M-16 for concrete. Cement
additives can have an effect on the air generated as measured using
these test methods. Undesirable air generation can lead to lower
strengths for concrete or mortar mixtures created from the cement.
Hence, for example, reflected IR data may be correlated with such
standard measurements.
In a ninth aspect of this eleventh example embodiment, the stored
data is based on the prehydration level of the cement particles
(which indicates the amount of water chemically absorbed onto the
surface of the cement particles). The prehydration level of the
cement particles may be quantified using Thermogravimetric Analysis
(TGA) and more specifically using a methodology to calculate Wk as
described in "Prehydration of cement: global survey and laboratory
results," in ZKG 6 (2018) by Silva, D. et al). Other
quantifications of prehydration levels may include the total weight
loss of the material expressed in percent weight.
In a tenth aspect of this eleventh example embodiment, the stored
data is based on reduction or burn conditions data of the cement
particles. During production of cement, changes to the kiln process
and the resultant clinker composition can lead to reduction, over
burn, and under burn conditions. Reducing `oxygen deficient` kiln
conditions can have a significant detrimental effect on the clinker
and the resulting cement performance in terms of strength, setting,
flow workability and kiln performance (fuel costs and maintenance).
Reduction causes a series of changes to the chemistry and
mineralogy of an affected clinker, including a raised orthorhombic
C.sub.3A content, and reduced alite reactivity etc. The level of
reduction in a specific clinker sample may be quantified using a
combination of methods. Firstly, by the determination of abnormal
changes in the actual clinker mineralogy determined by Quantitative
X-ray Diffraction by Rietveld (known as QXRD, or alternatively
XRD), as compared with the estimated qualities calculated from the
bulk elemental composition--Bogue analysis (See e.g., Bogue, "The
Chemistry of Portland Cement," Journal of Physical Chemistry, Vol.
52 (Reynolds Publishing Corporation (New York N.Y. 1947), which is
determined by X-ray Diffraction analysis (XRF). Such clinker
reduction can also be quantified by optical microscopy which can
confirm the presence of atypical changes to the clinker
microstructure (See e.g., Sibbick and Cheung, "Cement Clinker
Microscopy as an Aid to Determine Performance Differences in the
Presence of Chemical Additives, 36.sup.th International Cement
Microscopy Association Conference, Milan, Italy (2014)); and,
finally, by the use of chemical reduction tests such as the
Magotteaux test (See e.g., Hardtl, R., "Magotteaux test for cement
analysis, in Betonwerk+Fertigteil-Technik, Vol. 69 (2003), or
Manns, W., "Zur Braunverfarbung von Betonwaren--Moglichkeit der
fruhzeitigen Erkennung," Betonwerk+_Fertigteil-Technik, Vol. 68
(2002)). In a similar manner other cement kiln processes in terms
of degree of burning (over to under) and other factors (raw feed
residual issues, combinability, and cooling etc.) can be determined
primarily by optical microscopy (alite crystal size, free lime and
belite cluster contents, flux phase crystallinity) of the whole
uncrushed clinker. However, these microstructural and compositional
differences can also be verified by corresponding XRD and XRF
analyses. Underburned clinker typically exhibits a less than
optimum combination of the raw feed components into the primary
calcium silicate and calcium aluminate phases, leaving partially
burnt raw feed, undefined calcium silicate melt and higher than
optimum free lime components. Over-burned clinker typically
exhibits high levels of combination into large well-formed and
potentially lower reactivity alite crystals (>60 microns in
diameter) and correspondingly lower belite, free lime and flux
phases which can negatively impact late age strength
development.
In an eleventh aspect of this eleventh example embodiment, the
stored data is based on particle size distribution data of the
cement particles, which involves size of a given set of particulate
material. For example, the median or average particle size can be
determined based on the size distribution. Other values may be the
mass fraction of material above or below a given size, e.g. -32
micron represents the fraction of material below 32 microns, or the
specific surface area, as measured by the Blaine test or by a laser
diffraction PSD method. Furthermore, characteristics of the
Rosner-Ramler relationship, such as the slope can also be used.
Various particle size analysis instruments are commercially
available.
In a twelfth example embodiment, which may be based upon any of the
first through eleventh example embodiments above, the invention
provides a method wherein, in step (B), the at least one sensor
system is an infrared sensor system having an infrared emitter to
irradiate the ground blend of particles or finished cement and an
infrared sensor to detect infrared radiation reflected (IR) from
the irradiated ground blend of particles or finished cement, the
infrared sensor system thereby obtaining reflected IR data; and, in
step (C), the processor compares the reflected IR data with stored
reflected IR data corresponding to strength test data of hydrated
ground blend of particles or finished cement at a predetermined
age.
In an thirteenth example embodiment, which may be based upon any of
the first through twelfth example embodiments above, the invention
provides a method wherein, in step (B), the at least one sensor
system is an infrared sensor system having an infrared emitter to
irradiate the ground blend of particles or finished cement and an
infrared sensor to detect infrared radiation reflected (IR) from
the irradiated ground blend of particles or finished cement, the
infrared sensor system thereby obtaining reflected IR data; and, in
step (C), the processor compares the reflected IR data with stored
reflected IR data corresponding to exothermic data stored in
processor-accessible memory. The exothermic data is obtained by
calorimetric measurement, over a period of time, of hydrating
particle blends comprising ground clinker and source of calcium
sulfate, wherein (i) total heat output is stored; (ii) two
different exothermic time values are stored, a first value
corresponding to a time T.sub.1 indicating when the maximum
silicate reaction rate occurs after initiation of cement hydration,
a second value corresponding to a time T.sub.2 indicating the
visible onset of when either the renewed tricalcium aluminate
reaction rate occurs (if occurring after T.sub.1), or when the
completion of the aluminate reaction occurs (if occurring before
T.sub.1) after initiation of cement hydration; or (iii) both (i)
and (ii).
As used herein, the term "exothermic data" refers to temperature
data obtained using a semi-adiabatic, or, more preferably, heat
data obtained using an isothermal calorimeter (see e.g.,
commercially-available TAM.RTM. Air calorimeters). Typically, the
heat output is summed over a 24 or 48 hour period, but may be
measured for a longer period of time. A person skilled in the art
of cement hydration will understand that accurately measuring the
total heat output is not a trivial exercise. The measured heat
output is quite variable depending on how fast the operator
performing the test can properly mix the cement with water and
place the sample in the calorimeter, as well as the difference in
temperature between the calorimeter and the materials. Total heat
output can be calculated by summing the heat output starting from
an initial period of time (e.g. 1 hour, in which case the heat
output from time=1 to 24 hours is summed and considered the total
heat), or alternatively, starting from a time corresponding to the
minimum heat rate during the induction period. The total heat
generated is frequently correlated to a 1 day strength for a given
cement type (e.g. Blaine, chemistry, etc.).
The time values corresponding to specific events during the heat
evolution can provide an indication of the sulfate-aluminate
balance. Sulfate (frequently in the form of gypsum) is added to the
crushed clinker so that when water is added, the sulfate reacts
with the aluminate phases in the crushed clinker. This is the
primary aluminate reaction and happens on the order of seconds
after the water is combined with the cement. Based on the amount
and solubility of the gypsum (i.e. plaster is more soluble than
gypsum, and as temperature increases, gypsum becomes less soluble),
this primary aluminate reaction can be controlled, which allows a
silicate reaction to proceed. This silicate reaction is the main
contributor to the cement (and therefore concrete) strength gain.
In most cases, a silicate peak is visible when looking at the heat
flow rate over time during a calorimetry test (see e.g., the "X` in
FIG. 5C). The time at which this occurs is T.sub.1. If the
sulfate-aluminate balance is sufficient, a renewed aluminate
reaction will occur.
FIGS. 5A-E help to illustrate various hydration scenarios that can
arise by application of calorimetry testing. The figures illustrate
undersulfated to oversulfated states when the amount of sulfate
mixed in with a ground clinker is changed. Based on how close the
renewed aluminate reaction is to the silicate reaction, the onset
can be quite visible, or, on the contrary, it can be difficult to
discern. It can be revealed as a hump or shoulder (see hash mark
appearing at 11.23 hours in FIG. 5D), or a clear second peak (see
hump appearing to right of hash mark appearing at 10.05 hours in
FIG. 5C). Many methods exist for determining the onset of the
renewed aluminate peak, (e.g., ASTM C563-17, ASTM C1679-17).
Determination of onset is best when done on a consistent basis
(and, in this case, the T.sub.2 is identified as the local max of a
2.sup.nd derivative of the heat flow curve).
In a first aspect of the thirteenth example embodiment above, the
method of the present invention may involve, in addition to use of
the NIR sensor output, other information such as the gypsum
amount/feed rate, or other predictions (such as the predicted
gypsum amount, the predicted plaster amount, the predicted C.sub.3A
content, the predicted amount of the orthorhombic form of the
C.sub.3A mineral) that can also be combined with the NIR signal
output value to provide a more accurate prediction of the Delta
value. These other predictions can be provided based on the NIR
signal or other means (such as periodic XRD or XRF
measurements).
The orthorhombic form of C.sub.3A is interesting as it is
remarkably more reactive in the presence of sulfate than is the
alternate cubic crystal form. Its content is controlled by the
complex balance of sulfate and alkali in the kiln, which can be
affected not only by the raw material composition, but also by
changes in the fuel sulfur level as well as by reducing conditions
in the kiln, which tend to deplete the sulfate content by promoting
formation of sulfur dioxide gases which exit the kiln and are not
incorporated into the clinker. Due to the complexity of these
interactions, unexpected changes in the orthorhombic C.sub.3A
component can occur in relatively short time frames. The processor
can be programmed to make a comparison between a combination of
output signals from the NIR sensor as well as, for example,
C.sub.3A orthorhombic content (supplied by XRD, for example), to
data stored in processor-accessible memory, the stored data
previously obtained by irradiating finished cements to sense an
output NIR signal and accessing a C.sub.3A orthorhombic content.
Based on this comparison, a prediction of a physical or chemical
property of the corresponding finished cement can be made, or the
current prediction can be refined and updated.
In a fourteenth example embodiment, which may be based upon any of
the first through thirteenth example embodiments above, the
invention provides a method wherein, in step (C), the stored
reflected IR data corresponds to exothermic data comprising
calorimetric measurements of hydrating ground finished cement; the
method further comprising:
determining whether the difference between the time T.sub.2 minus
time T.sub.1 is less than (-)1 hours or greater than (+)4 hours,
where T.sub.1 represents the time at which maximum silicate
reaction rate occurs after initiation of cement hydration and
T.sub.2 represents the time after initiation of cement hydration at
which either the renewed tricalcium aluminate reaction rate occurs
(if after T.sub.1) or at which the aluminate reaction is completed
(if occurring before T.sub.1); and, if the difference of T.sub.2
minus T.sub.1 is less than (-)1 hours or greater than (+)4 hours,
adjusting the (i) amount, form or both amount and form of calcium
sulfate introduced into the grinding mill; (ii) classifier
settings, thereby to change relative amounts of ground particles
being sent to the silo and being recirculated back into the
grinding mill; (iii) amount, type, or both amount and type of
cement additives introduced into the grinding mill; (iv) amount of
water being introduced into the grinding mill; (v) amount of air
provided by adjusting power or speed of a fan or blower connected
to ventilate the mill; (vi) amount or type of supplemental
cementitious material introduced into the grinding mill; (vii)
cement cooler setting, thereby to change the temperature of the
finished cement or (viii) combination of any of the foregoing.
In a first aspect of the fourteenth example embodiment, the method
involves determining whether the difference between time T.sub.2
minus time T.sub.1 is less than 0 and greater than 3 hours; and, if
the difference is less than 0 and greater than 3 hours, then any of
the aforementioned adjustments or combination of adjustments can be
made, based upon any of the aforementioned grinding mill
conditions.
In a second aspect of the fourteenth example embodiment, the method
involves determining whether the difference between time T.sub.2
minus time T.sub.1 is less than 0.5 and greater than 2.5 hours;
and, if the difference is less than 0.5 and greater than 2.5 hours,
then any of the aforementioned adjustments (or combinations
thereof) can be made, based upon any of the aforementioned grinding
mill conditions. A Delta between 0.5 and 2.5 hours typically
maximizes the 1 day strength of the clinker. This range shifts if
other performance targets are desired, for example, if later age
strength are to be maximized, the Delta should be increased by 1-2
hours. Once the finished cement reaches the customer, addition of
fly ash or clays (e.g. calcined clays) to the concrete mix can add
additional aluminates to the cementitious system. In this case, the
sulfate-aluminate balance will be shifted. A shift can also occur
if the cement is cast at elevated temperatures. In this case, the
increased temperature increases the reactivity of the aluminate,
but decreases the solubility of the sulfate. This leads to an
under-sulfated situation. In order to prevent this situation from
occurring, the Delta target in the cement plant may be shifted to
the right (increased). Thus, inputs from the field can be used to
adjust the target Delta.
In a fifteenth example embodiment, which may be based upon any of
the first through fourteenth example embodiments above, the
invention provides a method wherein, in step (C), the stored
reflected IR data corresponds to exothermic data comprising
calorimetric measurements of hydrating ground finished cement; the
method further comprising:
determining whether the difference between the time T.sub.2 minus
time T.sub.1 is less than the predefined target minus 1 hour or
greater than the predefined target plus 2 hour, where T.sub.1
represents the time at which maximum silicate reaction rate occurs
after initiation of cement hydration and T.sub.2 represents the
time after initiation of cement hydration at which either the
renewed tricalcium aluminate reaction rate occurs (if after
T.sub.1) or at which the aluminate reaction is completed (if
occurring before T.sub.1); and, if the difference is less than the
predefined target minus 1 hour or greater than the predefined
target plus 2 hour, (i) amount, form or both amount and form of
calcium sulfate introduced into the grinding mill; (ii) classifier
settings, thereby to change relative amounts of ground particles
being sent to the silo and being recirculated back into the
grinding mill; (iii) amount, type, or both amount and type of
cement additives introduced into the grinding mill; (iv) amount of
water being introduced into the grinding mill; (v) amount of air
provided by adjusting power or speed of a fan or blower connected
to ventilate the mill; (vi) amount or type of supplemental
cementitious material introduced into the grinding mill; (vii)
cement cooler setting, thereby to change the temperature of the
finished cement or (viii) combination of any of the foregoing.
In a first aspect of the fifteenth example embodiment, the method
involves determining whether the difference between time T.sub.2
minus time T.sub.1 is less than the predefined target minus 0.5
hours or greater than the predefined target plus 1.5 hours; and, if
the difference is less than the predefined target minus 0.5 hours
or greater than the predefined target plus 1.5 hours, then any of
the aforementioned adjustments (or combinations thereof) can be
made, based upon any of the aforementioned grinding mill
conditions.
In a second aspect of the fifteenth example embodiment, the method
involves determining whether the difference between time T.sub.2
minus time T.sub.1 is less than the predefined target minus 0.25
hours or greater than the predefined target plus 1 hour; and, if
the difference is less than the predefined target minus 0.25 hours
or greater than the predefined target plus 1 hour, then any of the
aforementioned adjustments (or combinations thereof) can be made,
based upon any of the aforementioned grinding mill conditions.
The optimum Delta to maximize the strength is variable. While it is
frequently in the time ranges identified above, so they represent
appropriate starting point targets, various factors can alter it.
For instance, if aluminate activity in the clinker or SCM
increases, but the sulfate in the cement is in the form of more
slowly soluble gypsum, a greater amount may be needed to increase
the amount of sulfate that can dissolve at early times, and thus
control the very early aluminate reactions so the silicate
hydration is not restricted. This greater amount of gypsum for
optimum strength would lead to a greater Delta, even though the
actual time this extra gypsum was needed was much earlier. The
ability of the present invention to detect such a change in clinker
or SCM composition and adapt composition or mill control settings
to accommodate the change is one of its key advantages.
In a sixteenth example embodiment, which is based upon any of the
first through fifteenth example embodiments, the method further
comprises comparing sensor data taken from step (B) to at least two
different stored processor-accessible data sets. For example, in
step (C), the sensor output signals obtained in step (B) are
compared to two different types of stored data relating to
different cement attributes or properties; or, as another example,
relating to two different time periods from which the data was
collected. It is possible that adjustments to processing conditions
to change the strength will result in changes to Delta and vice
versa. For example, if the Blaine specific surface area is
increased to increase the strength, the ground clinker will become
more reactive in terms of the aluminate phases, which will shift
the Delta to lower time values. Thus, more sulfate may be added to
compensate. Preferably, comparisons and subsequent adjustments are
made in an iterative fashion.
In a first aspect of the sixteenth example embodiment, the at least
two or more comparisons made in step (C) are further compared with
respective targets; and based on the deviations from the respective
targets, a processor selects adjustments and the order of
adjustments, wherein the adjustments comprise (i) the amount, form
or both amount and form of calcium sulfate introduced into the
grinding mill in step (A); (ii) the classifier setting, thereby to
change relative amounts of ground particles being sent to the silo
and being recirculated back into the grinding mill; (iii) the
amount or type of cement additives introduced into the grinding
mill; (iv) the amount of water being introduced into the grinding
mill; (v) the amount of air provided by adjusting the power or
speed of a fan or blower connected to ventilate the mill; (vi) the
amount or type of supplemental cementitious material introduced
into the grinding mill; (vii) the cement cooler setting, thereby to
change the temperature of the finished cement, or (viii) a
combination of any of the foregoing.
In a seventeenth example embodiment, which may be based upon any of
the first through sixteenth example embodiments above, the
invention provides a method further comprising measuring the
particle size of the clinker and calcium sulfate being ground in
the grinding mill; and, in further response to the step (C)
comparison between the obtained reflected IR data and the stored
reflected IR, adjusting a particle size characteristic or property
of the clinker and calcium sulfate being ground, or both.
In a first aspect of this seventeenth example embodiment, IR data,
and more specifically, NIR data is used to predict a particle size
characteristic of the ground cement, such as specific surface area
(measured as, for example, Blaine), average particle size,
D.sub.x10, D.sub.x50, D.sub.x90, D.sub.[4,3], D.sub.[3,2], span
90-10, -32 micron, -45 micron, specific surface area, alpine (See
e.g., M. C. Pasikatan et al., J. Near Infrared Spectrosc. 9,
153-164 (2001)), and the method involves making an adjustment to
change particle size characteristic or distribution. If detected IR
values do not match stored values corresponding to a desired
particle size, for example, an adjustment can be done by altering
classifier settings so as to obtain the desired particle size
characteristic.
In a second aspect of this seventeenth example embodiment, data
based on laser diffraction measurements can be similarly used to
predict particle size characteristics of the ground cement, and
similarly this can be compared to stored values, such that if
measured laser diffraction values do not match stored laser
diffraction values corresponding to a desired particle size
characteristic, for example, an adjustment can be done by altering
classifier settings so as to obtain the desired particle size
characteristic(s).
In a third aspect of this seventeenth example embodiment, periodic
data collected using the LD sensor system, which may be offline,
can be used to update or refine the NIR calibration for prediction
of a particle size characteristic of the ground cement.
In a fourth aspect of this seventeenth example embodiment, periodic
data collected using a temperature sensor, moisture sensor, XRD,
XRF, PGNAA or a combination thereof, which may be offline, can be
used to update or refine the NIR calibration for prediction of a
particle size characteristic of the ground cement. For example,
XRD, XRF, PGNAA may give indications of iron which can help
interpret the NIR signal.
In an eighteenth example embodiment, which may be based upon any of
the first through seventeenth example embodiments above, the
invention provides a method further comprising calculating a value
corresponding to degree or level of prehydration of the cement,
incorporating the value into processor-accessible memory, and
initiating a decision whether to adjust the grinding mill or
recirculation process conditions, and adjusting at least one of
grinding mill or recirculation process conditions. For example, in
step (B), the at least one energy radiation/sensor system is an
infrared sensor system having an infrared emitter to irradiate the
ground blend of particles or finished cement and an infrared sensor
to detect infrared radiation reflected (IR) from the irradiated
ground blend of particles or finished cement, the infrared sensor
system thereby obtaining reflected IR data; and, in step (C), the
processor compares the reflected IR data with stored reflected IR
data corresponding to test result data indicating the degree or
level of prehydration the cement.
In a first aspect of this eighteenth example embodiment, the method
involves comparing output signal from IR sensor to stored data and
calculating the degree or level of cement prehydration, the stored
data being previously obtained by heating cement samples and
measuring the weight loss within a defined temperature range. The
prehydration level is most accurately measured using a
thermogravimetric analysis (TGA) instrument.
The quantitative measurement of "prehydration" level may be better
appreciated with reference to FIG. 7, which illustrates both the
weight change of cement as a function of temperature as well as the
derivative of the change in weight with respect to temperature as
the cement is heated from room temperature to at least 450.degree.
C. The prehydration level, designated by the symbol Wk, defined as
the percentage mass loss of a cement sample as it is heated,
starting just after the gypsum finishes dehydrating (about
125.degree. C. in the example in FIG. 7) and finishing just before
the portlandite (calcium hydroxide Ca(OH).sub.2) starts to
decompose (about 350.degree. C. in the example in FIG. 7).
In a second aspect of the eighteenth example embodiment, based on
the prehydration level measurement (e.g., Wk), an adjustment is
made to (i) the amount of water being introduced in the grinding
mill in step (A), (ii) the amount of chemical additive introduced
in the grinding mill in step (A), (iii) the amount of air provided
(by adjusting the power or speed of the fan connected to ventilate
the mill); (iv) the amount of cooling provided by the cement
cooler; or (v) a combination thereof.
In a third aspect of the eighteenth example embodiment, a further
comparison is made, which is based on a predefined relationship
between the prehydration level and the Delta of the cement, the
amount and/or type of sulfate (which is determined based on the
comparison made in step (C)) is adjusted in response to a change in
the measured prehydration level of the cement (which is based on a
separate comparison made in step (C)), to correct Delta value so
that it more accurately corresponds to or matches a predetermined
target value. This can be performed as an iterative process.
In a fourth aspect of the eighteenth example embodiment, based on a
predefined relationship between prehydration level and the strength
of the cement (e.g. at the age of 1 day), the fineness or other
parameters (as previously discussed) affecting strength is adjusted
in response to a change in the measured prehydration level of the
cement, to control the strength up or down to match a predetermined
target value. This can be performed as an iterative process.
In a nineteenth example embodiment, which may be based upon any of
the first through eighteenth example embodiments above, the
invention provides a method wherein, in step (B), the at least one
energy radiation/sensor system is an infrared sensor system having
an infrared emitter to irradiate the ground blend of particles or
finished cement and an infrared sensor to detect infrared radiation
reflected (IR) from the irradiated ground blend of particles or
finished cement, the infrared sensor system thereby obtaining
reflected IR data; and, in step (C), the processor compares the
reflected IR data with stored reflected IR data corresponding to
test result data, and indicates on a monitor display, print out, or
by visual or audible alarm when the degree of reduction in the
clinker meets or exceeds a pre-established threshold value.
A reducing kiln environment (oxygen deficient) beyond a threshold
can have a significant detrimental effect on the performance
(strength) of the clinker produced and the resulting cement. A
number of factors can influence the development of reducing
conditions. Changes in raw meal composition, grind (size) and feed
rate (and flow) can affect the oxygen consumption rate and thus the
conversion of the kiln conditions from oxygen-rich to
oxygen-deficient environment, without any changes to the other
variables in the system. The other variables which can also
influence the kiln conditions include changes in fuel type
(calorific values, coal to petcoke, use of alternative fuels) and
changes to kiln process (flame position and shape, air flow rates
and sources, temperature etc.). To train the NIR to predict
reduction, the test result can be obtained from a chemical
reduction test such as the Magotteaux test (see e.g., Hardtl, R.,
"Magotteaux test for cement analysis, in
Betonwerk+Fertigteil-Technik, Vol. 69 (2003), or Manns, W., "Zur
Braunverfarbung von Betonwaren--Moglichkeit der fruhzeitigen
Erkennung," Betonwerk+_Fertigteil-Technik, Vol. 68 (2002)), or on
results from chemical analysis such as XRD, XRF, and even
furthermore from microscopy analysis.
In a twentieth example embodiment, the present invention provides a
system for manufacturing cement, comprising:
a grinding mill for grinding raw materials including clinker, a
source of sulfate chosen from gypsum, plaster, calcium anhydrite,
or a mixture thereof, and optionally cement additives, to produce a
ground blend of particles comprising ground clinker and calcium
sulfate;
a classifier for separating the ground blend of particles whereby a
first portion of the particles or the finished cement are sent to a
silo or other receptacle for containing the finished cement and
whereby a second portion of the particles is recirculated into the
grinding mill for further grinding;
at least one sensor system chosen from infrared sensor system,
laser diffraction sensor system, or both, for detecting emanation,
reflectance, transmittance, or absorption of energy by or through
the ground blend of particles or finished cement, and generating
output signals corresponding to the detected energy; and
a processor configured or programed to compare output signals
generated by the at least one sensor system with data stored in
processor-accessible memory, the stored data comprising output
signal values previously obtained from sensors measuring the
emanation, reflectance, transmittance, or absorption of energy in
the infrared spectrum, laser diffraction spectrum, or in both the
infrared and laser diffraction spectrums (the stored data being
correlated with a physical or chemical property of the
corresponding finished cement, hydrated cement or cementitious
product made with the cement, e.g., (i) strength test data, (ii)
exothermic data; (iii) set initiation data; (iv) slump data; (v)
dimensional stability data; (vi) air content data; (vii)
prehydration level data; (viii) reduction or burn conditions data;
(ix) cement particle size distribution data; or (x) a combination
thereof); and
the processor further configured or programed to adjust (i) amount,
form, or both amount and form of calcium sulfate introduced into
the grinding mill; (ii) classifier setting, thereby to change
relative amounts of ground particles being sent to the silo and
being recirculated back into the grinding mill; (iii) amount, type,
or both amount and type of cement additives introduced into the
grinding mill; (iv) amount of water being introduced into the
grinding mill; (v) the amount of air provided by adjusting power or
speed of a fan or blower connected to ventilate the mill; (vi)
amount or type of supplemental cementitious material introduced
into the grinding mill; (vii) the cement cooler setting, thereby to
change the temperature of the finished cement, or (viii)
combination of any of the foregoing (e.g., in order to modify a
physical or chemical property of the finished cement).
In various exemplary aspects of the above-described nineteenth
example embodiment, the system of the invention may incorporate
various exemplary features and aspects as previously described for
the second through eighteenth example embodiments as described
above.
In a twenty-first example embodiment, which may be based on any of
the foregoing first through twentieth example embodiments, the
invention provides a method or system which comprises, steps and/or
components for:
(A) providing an indication (e.g., audible or visual alarm or
indication, monitor or hand-held display, text message, email,
etc.) that a physical or chemical property or amount of the raw
materials, raw meal, clinker, the source of calcium sulfate, the
chemical additive, the SCM, or the finished cement has changed;
(B) performing at least one test to determine a physical or
chemical property on the finished cement chosen from (i) strength
test data, (ii) exothermic data; (iii) set initiation data; (iv)
slump data; (v) dimensional stability data; (vi) air content data;
(vii) prehydration level data (i.e., measurement of amount or
degree of chemical change and/or reaction product formed on cement
particle surface due to reaction between absorbed moisture and
certain phases of the cement); (viii) reduction or burn conditions
data; (ix) cement particle size distribution data; and (x) a
combination thereof;
(C) detecting from the finished cement tested in step (B) using at
least one sensor system chosen from infrared sensor system, laser
diffraction sensor system, or both; the at least one sensor system
providing output signals corresponding to the reflectance,
transmittance, or absorption of energy by or through the ground
blend of particles or finished cement; (D) storing both the test
results of (B) and (C) into a database accessible by a processor;
and (E) making an adjustment to a model predicting at least one of
physical or chemical properties listed above in subparts (B(i))
through (B(ix)), making an adjustment to a target value for at
least one of (i) through (ix) or both.
In a first aspect of this twenty-first example embodiment, the
indication is (i) a change in the fuel source; (ii) a predefined
deviation from a chemical property as measured by IR, LD, QXRD,
XRF, PGNAA or a combination thereof; (iii) a predefined deviation
in the mill temperature or humidity; (iv) a predefined deviation in
the relative raw materials entering the kiln; (v) a change in a
kiln processing condition; (vi) a change in a mill processing
condition; or (vii) a notification that a manual or automated
cement sample was taken.
In a second aspect of this twenty-first example embodiment, the
sample is obtained via an autosampler and more preferably, a sample
obtained via an autosampler that is not composited over time.
In a third aspect of this twenty-first example embodiment, the
indication is a change in any predicted value derived from a
comparison between an IR signal and (i) strength test data, (ii)
exothermic data; (iii) set initiation data; (iv) slump data; (v)
dimensional stability data; (vi) air content data; (vii)
prehydration level data; (viii) reduction or burn conditions data
or; (ix) cement particle size distribution data; or (x) a
combination thereof.
In a fourth aspect of the twenty-first example embodiment, the
model is adjusted by recalibrating the model with the new data. The
comparison described for step (C) of the first example embodiment
can be performed through use of look up tables or by using
algorithms configured to generate predicted test results. For
example, this can be done by using the NIR signal output value to
identify a similar signal stored in the memory and retrieve the
associated test result data. This can also be done by using a
mathematical function, based on the NIR, LD, T, M/RH sensor values,
to generate a predicted test result value (e.g., a strength value).
The algorithm or mathematical function can be derived based on
standard regression techniques such as linear regression, partial
least squares regression, regression techniques combined with
principal component analysis or factor analysis approaches, or even
machine learning, which includes both supervised (e.g. support
vector machines, Bayesian methods, random forest methods, etc.) and
unsupervised machine learning methods (k-means clustering, neural
networks, etc.).
In a twenty-second example embodiment, which may be based on any of
the foregoing first through twenty-first example embodiments, the
invention provides a system and method of analyzing the performance
of a cement, comprising: steps and/or system for (A) detecting from
a ground blend of particles or finished cement obtained from step
(A) using infrared sensor system output signals corresponding to
the emanation, reflectance, transmittance, or absorption of energy
by or through the ground blend of particles or finished cement; (B)
comparing, using a processor, output signals provided by the
infrared sensor system to data stored in processor-accessible
memory, the stored data previously obtained by detecting from the
finished cements by at least one sensor system (the stored data
being correlated with a physical or chemical property of the
corresponding finished cement, hydrated cement or cementitious
product made with the cement, e.g., (i) strength test data, (ii)
exothermic data; (iii) set initiation data; (iv) slump data; (v)
dimensional stability data; (vi) air content data; (vii)
pre-hydration level data, or; (viii) reduction or burn conditions
data; (ix) cement particle size distribution data; and (C)
returning a predicted physical or chemical property of the
corresponding finished cement.
In a first aspect of the twenty-second example embodiment, at least
two physical or chemical properties of the cement are predicted
from the infrared sensor system output signal.
The invention can be embodied in many different modes and should
not be construed (nor should expressions regarding what the
"invention is or provides" be construed) as a limitation to the
exemplary embodiments set forth herein; rather, these embodiments
are provided so that this disclosure will be thorough and complete
and fully convey the scope of the invention to those of ordinary
skill in the art.
EXEMPLIFICATIONS
In a first example, an illustrative method and system of the
invention for adjusting sulfate levels in grinding manufacture of
cement is outlined in the flow chart of FIG. 8 and illustrated in
FIG. 9.
In block 102 of FIG. 8, a cement grinding mill (212 of FIG. 9)
(e.g. a ball mill, vertical roller mill, etc.) is fed a combination
of clinker (214), a source of sulfate (e.g. gypsum) (216), and
optionally one or more SCMs (e.g. fly ash, slag) (218) and/or
cement additives (e.g. strength enhancers, grinding aids, set
modifiers, workability modifiers, sodium sulfate, chromium
reducers) (220) at known rates, and exposed during the milling
process to a water spray (222) at a known rate and a ventilation
fan (224) set at a known speed. A computer processor (226) receives
information about the feed rates and characteristics of each
component (e.g. an identifying name). Furthermore, a near infrared
(NIR) sensor (228) can obtain a reflection signal from the clinker,
SCM and sulfate sources independently or as a group. These signals
can be sent to and then analyzed by the processor via predetermined
lookup tables or correlation functions to determine features such
as alkali sulfates from the clinker; aluminate content from the
SCM; gypsum/anhydrite ratios from the sulfate source (plaster is
formed by dehydration of the gypsum during the milling process).
For the chemical additive, identifiers (e.g. product name) or
detailed information about the formulations (e.g. TEA content) can
also be sent to the processor.
In block 104 of FIG. 8, the processor also receives information
about the mill output volume as well as NIR spectra (230 of FIG.
9), a laser diffraction (LD) signal (232) and optionally a
temperature, moisture or humidity (234) from the finished cement
exiting the mill or optionally a temperature, moisture or humidity
(254) from the chimney (260). These signals (including those on the
SCM/sulfate/etc.) can be collected, for example, every minute. The
multiple real-time NIR spectra can be collected using the same NIR
spectrometer via input from different sensor channels. For example,
the Bruker MATRIX-F FT-NIR spectrometer allows collection of
signals from six different sensors. The signals are collected using
sensor heads that transfer the signal to the spectrometer using
fiber optic cables which preserves signal quality. This allows not
only multiple sampling points, but also, allows the spectrometer
itself to be placed in a protected area free from cement dust and
other harmful elements (e.g. humidity and heat).
For NIR sensors situated to monitor material being carried on
belts, the distance between the surface of the material (e.g.,
cement or SCM) bed and the sensor can vary with time as the
material bed passes below the sensor. This can affect the measured
NIR signal. A protective casing made of an optically clear (e.g.
low light absorbance) material such as quartz, sapphire, or glass
can be used to submerge the sensor within the material particles.
This can allow the distance between the sensor and the material
particles to remain constant.
Alternatively, a distance sensor, such as an ultrasonic range
finder, can be installed next to the NIR detector so that a
distance measurement can be made and used to adjust the NIR
measurement or prediction in real time. Such a range finder is
commercially available under the ULTRASONIC.RTM. brand (See e.g.,
https://www.maxbotix.com/Ultrasonic_Sensors.htm). Aside from the
distance of the material to the detector, the material bed depth
should be sufficient depending on the internal setup of the NIR
instrument. In most cases, a bed height of more than 1 cm is
sufficient.
Cement and other fine particulates can also be transported via a
pneumatic tube or with air slides or other air-flow channels
instead of a moving belt. In this case, an optically clear window
can be installed in-line with the tube (or on a bypass tube
connected to the tube). NIR signals can then be collected. For NIR
instruments situated to monitor air slides, the concentration of
the fluidized bed particles may affect the NIR signal. In this
case, the NIR signal may be adjusted based on changes in parameters
such as the air slide flow rate.
Preferred for use in the present invention are IR detectors suited
to measure diffuse light (e.g., light that is scattered by a
particle bed).
The system may also include more than one NIR sensor. In one
example, different NIR sensors may be programmed to only scan a
narrow window of wavelengths to improve the speed and/or accuracy
at which the spectra is collected. For example, one NIR may be
dedicated to determine a gypsum amount while another may be
dedicated to a Delta measurement. It may be that different
predictions of parameters (e.g. Delta or strength) require
different spectral ranges or values. It is also possible to program
a wavelength hopping scheme, where discrete regions of the
wavelength spectra is collected instead of the entire spectra.
An example of an NIR signal is shown in FIGS. 10A-D. A raw signal
is given in FIG. 10A over a wavenumber range between 4000 and 12000
cm.sup.-1. The raw intensity is reported. In FIG. 10B, a standard,
normal variate transformation is applied to normalize the baseline.
In FIGS. 10C and 10D, the first and second derivatives are given
respectively. In the generation of predictive models, one or more
of these signals can be used as inputs for the model.
Based on the NIR signal, properties of the finished cement can be
determined using lookup tables or correlation functions. These
correlation functions or models can be generated using several
standard techniques including multiple linear regression,
multivariate regression, principal component regression, partial
least squares regression, machine learning or other methods. For
example, a well-known technique used to develop NIR correlations
(to species concentrations), is partial least squares regression
(PLS). See e.g., Wold, S.; Sjostrom, M.; Eriksson, L. (2001).
"PLS-regression: a basic tool of chemometrics". Chemometrics and
Intelligent Laboratory Systems. 58 (2): 109-130, and U.S. Pat. No.
5,475,220, which is specific to cement phase analysis. Other
approaches may involve for example, Fourier transforms (see, e.g.
McClure, W. F.; Hamid, A.; Giesbrecht, F. G.; Weeks, W. W.; (1984).
"Fourier analysis enhances NIR diffuse reflectance spectroscopy."
Applied Spectroscopy. 38 (3): 322-328), and machine learning
methods (See e.g., Borin A.; Ferrao M. F.; Mello C.; Maretto D. A.;
Poppi R. J.; (2006). "Least-squares support vector machines and
near infrared spectroscopy for quantification of common adulterants
in powdered milk." Analytica Chimica Acta. 579 (1): 25-32).
These models or lookup tables are constructed by obtaining NIR
signals from multiple cement samples and measuring the desired
property of interest (e.g. strength or setting time) for the
corresponding hydrated cement samples (in the case of strength, for
example) or unhydrated samples (in the case of a fineness parameter
or pre-hydration, for example). As association is then made between
the NIR signal and the property of interest, allowing the property
to be predicted just from the NIR signal.
In addition to the predicted properties from the received NIR
signals on the finished cement, the LD signal is used to determine
a fineness characteristic of the cement (e.g. specific surface
area, mean particle size, fraction below a certain sieve size,
etc.). See e.g. the Insitec particle size analyzers commercially
available from Malvern. This fineness characteristic is more
preferably obtained from the NIR signal.
Based on the predictions from the NIR and LD signals, the finished
cement produced can be adjusted towards one or more desired
targets. For example, a finished cement may require to meet both a
Delta target and strength target. Although maximum targets can be
specified, in general, a balance of multiple properties is desired,
which may not be the optimum for any one property. More desirable
may be a consistent cement product. Thus, for example, a Delta of 2
hours with a strength of 42.5 MPa may be a target for a given
finished cement.
The target can be assigned in multiple ways depending on the cement
producer's preferences or needs. For example, a cement producer may
be producing a cement with a certain class of strength (e.g. class
42.5 (minimum strength of 42.5 MPa, maximum strength of 62.5 MPa at
the age of 28 days). Targets for Delta can also be determined using
standards such as ASTM C563-17 tests or equivalent. In these cases,
it is possible to use sulfate contents corresponding to the
strength or calorimetry results and combine these data with NIR
signals of the corresponding cement (the NIR signals obtained
before hydrating the cement). The inventors have found that the
optimum Delta, (i.e. the Delta corresponding to the highest
strength) can be predicted based on the NIR signals. This provides
an enormous advantage as both the target Delta and the current
Delta (with a given amount of sulfate added) can be predicted in
real-time. Currently, there is no method to provide a real-time
optimum Delta. Still, the cement producer may also tailor, for
example, their Delta to the region or market that they are selling
to. In warmer climates a higher temperature may lower the
solubility of plaster. If plaster has been used to control rapid
aluminate reaction a sulfate deficiency may result. Furthermore,
the reactivity of the aluminates increase, which can greatly
increase the susceptibility to flash setting or extended set.
Therefore, the cement producer may want an increased Delta. As
another example, if the cement producer's market typically produce
cement which is later combined with high volumes of class C fly
ash, an increased Delta may also be desired to avoid common flash
setting or extended set with class C fly ash (as the fly ash
contributes more aluminate to the overall cementitious system
without enough sulfate to balance). Or, the cement producer may
decide to make an adjustment to the NIR-predicted optimum Delta. In
other words, as the NIR-predicted optimum may indicate the Delta
required to optimize strength, the producer may want to increase
the Delta by, for example, 1 hour from this optimum Delta in order
to account for the region (e.g. a warmer climate where the Delta
will be reduced) or market (e.g. where fly ash is frequently added
to the concrete and will supply extra aluminate that will lead to a
reduced Delta). Targets may also be assigned to meet other related
constraints, such as cost, carbon dioxide emissions, workability
retention, admixture response, achievement of required early
strength without exceeding statutory maximum strength, etc.
In FIG. 11, optimum Delta values predicted based on NIR signals are
compared to actual measured optimum Delta values on the
corresponding cements. Ten individual clinkers were crushed in a
laboratory ball mill. Each crushed clinker was then blended with
various levels of gypsum and plaster. For each blend, an NIR signal
was obtained using a Bruker MATRIX-F FT-NIR spectrometer. Output
signals similar to those in FIGS. 10A through 10D were obtained. In
addition, for each blend, a mortar specimen was created according
to EN-196-1:2016, which includes mixing with a standard sand sample
and water to cement ratio. Various properties such as workability,
air, strength, and Delta were obtained. Delta values were obtained
through analysis of heat flow curves generated by a TAM.RTM. Air
calorimeter, generating output signals similar to those of FIGS. 5A
through 5E. In order to develop the NIR output signal--optimum
Delta relationship shown in FIG. 11, the maximum strength (in this
example, the compressive strength after 1 day) was determined for a
set of crushed clinker with different sulfate levels, each with a
different, measured Delta. The optimum Delta, therefore,
corresponds to the maximum strength attained. This optimum Delta is
valid for a given clinker (which was produced at a given instance
in time). Data sets including the NIR output signals and the
measured optimum Delta values were partitioned into
cross-validation sets, using a repeated-stratified K-fold method.
For each set, a partial least-squares (PLS) model was fit to a
training partition, and validated on the remaining data (the
testing partition). In implementing the PLS model, the number of
components yielding the best fit according to the average accuracy
over all the cross-validation sets was chosen. This PLS was then
applied to all of the data and the fit is shown in FIG. 11. In FIG.
11, the predicted optimum Delta is plotted against the actual
measured optimum Delta, with the solid line representing a
one-to-one relationship. For this particular model, applied over
432 points, over 91% of the predicted values were within 0.5 hours
of the actual measured values. Note that this prediction is valid
over a large range of clinker chemistries and physical properties
(e.g. Blaine specific surface area).
In addition to targets given for Delta and strength based on, for
example, NIR predictions or fineness characteristics, ancillary
limits can be provided to prevent certain processes from leading to
suboptimal cement properties or mill conditions. For example, a
maximum and minimum gypsum feeder rate, or rates of change of such
feeder rate can be established. Likewise, limits on the water spray
and ventilation fan speed can be enforced. Because the
relationships between for example the water spray, pre-hydration
level, and gypsum dehydration can be complex, limiting the process
can limit unexpected interaction issues (e.g. the water spray rate
or the cement cooler may affect both temperature and moisture in
the mill). These limits can help to prevent runaway conditions
where catastrophic results may occur.
In order to achieve the targets, predictions of both Delta and
strength may be determined. In FIG. 12, Delta values predicted
based on NIR signals are compared to actual measured Delta values
on the corresponding cements. The model was generated using the
same cement sets that the optimum Delta was calculated from, which
again includes ten individual clinkers. For this particular model,
applied over 365 points representing ten individual clinkers, 98%
of the data was predicted within 0.5 hour of the actual measured
value. Note that this has been performed over a very wide range of
clinker chemistries (represented by the shape of the data point),
sulfate levels and Blaine specific surface areas (represented by
the shade of the data point) and surprisingly has shown a very high
accuracy. It is expected that within a given plant, the range of
both clinker chemistries and specific surface areas will be
narrower than the data used to generate FIG. 12, which may lead to
improvements in accuracy. Thus, based on the prediction, a current
Delta value of the finished cement can be determined. Based on a
deviation from the target, several different options can be taken.
For example, in the event that the Delta is greater than the
target, the sulfate content can be reduced. The amount of reduction
can be determined based on a predetermined relationship between a
sulfate dose and Delta. However a more preferred method is to make
a small adjustment in the sulfate content (in this case a
reduction) that is large enough to be detected by the NIR signal,
but small enough not to cause a catastrophic change in the cement
properties (i.e. to avoid under- or over-dosing). After the change
has been made, another NIR signal and prediction can be executed to
measure the deviation of the Delta with respect to the target. This
process can be repeated until the Delta is within a predefined
distance from the target. A similar process can be performed if the
Delta is less than the target (e.g. the sulfate source can be
incrementally increased). Moreover, the invention allows not only
the total sulfate, but the amounts of gypsum and plaster to be
adjusted. The plaster content is not as straightforward as adding
or subtracting the sulfate source because there are cases where a
given total sulfate content is required along with a specific
gypsum to plaster ratio. In these cases, changes to the mill
processing parameters can be performed, thus affecting the amount
of gypsum dehydration to plaster. For example, if the
gypsum/plaster ratio is to be decreased, the temperature in the
mill can be increased and/or the water spray rate can be decreased.
However, the mill system is complex and this action may affect
pre-hydration or other factors affecting strength. It is with such
system complexities that a real-time measurement of both Delta and
strength enables true control.
As another method of control, an evolutionary optimization scheme
can be implemented. Evolutionary optimization is an artificial
intelligence algorithm inspired by biological evolution. Related to
the present invention, small actions, which may be random, are
taken to introduce a change to the cement production process.
Measurements are made (through the use of NIR, for example) to
determine the effects of the small actions. Because measurements
can be made in real-time, many small actions can be taken. Each
action and measurement is recorded and the algorithm begins to
learn the best way to optimize toward a pre-defined goal, for
example to achieve a strength target of 42.5 MPa and a Delta of 2
hours. This method provides an advantage over a traditional
optimization method, since traditional methods rely on
understanding accurate relationship between actions and the changes
measured (e.g. increasing Blaine and achieving a certain change in
strength as measured by NIR). Because of the complexity of the
system, understanding both the relationships and the interaction
effects (e.g. changes in Delta as they affect changes in strength
and vice versa) is very difficult.
As a second example, in FIG. 13, strength values predicted based on
NIR signals are compared to actual measured strength values on
corresponding cements. The model was generated using the same
cement sets that the Delta was calculated from, which again
includes ten individual clinkers. In this case, after the PLS model
was generated (in the same fashion as described above), 77% of the
predicted values fall within 5% of the actual measured strength.
This is a surprisingly high degree of accuracy considering that the
correlation function used to make the prediction was developed
using a wide range of clinker chemistries (represented as the shape
of the data point) and Blaine specific surface areas (represented
as the shade of the data point). It is expected that when the range
of variation in the clinker and cement properties is lower, as
would be expected when only measuring the cement made from a single
plant using clinker from the same kiln, the accuracy should
improve. This is supported by FIG. 14, which shows that the
accuracy is higher when only one clinker source is considered, at
similar Blaine specific areas (98% of the predicted values fall
within 5% of the actual measured strength). To the inventors'
knowledge, a direct relationship between strength and NIR signals
has not previously been demonstrated.
With a strength prediction as shown in FIG. 13 or 14, not only can
the deviation from a target strength be determined, but the change
in strength relative to the Delta can also be determined. Thus, an
iterative approach is possible where both the predicted Delta and
strength are constantly monitored in conjunction with other
possible measured parameters, and adjusted, leading to an
understanding of how optimum Delta varies with other factors. The
present invention enables this on a frequency basis on the order of
minutes, which is of the same order of magnitude as the cement
residence time in the mill. Furthermore, this also enables each
adjustment (to one or more parameters/processes) to be of small
increment, because the application of online sensors allow
prediction of both Delta and strength a multiplicity of times over
a short period of minutes, strengthening the statistical confidence
in the direction of performance change brought about by said small
adjustment. Having confidence in the result of the adjustment,
further adjustments can be made. Such a method allows a rapid
iterative process to accommodate changes in the clinker, sulfate
source, SCM, additive performance, etc. This is a distinct
improvement over what is available to cement producers today. For
example, if a cement producer were today using calorimetry to
control to a pre-determined optimum Delta, the Delta could be known
at best every 8-16 hours (depending on when the Delta actually
occurs in the cement). This has two distinct disadvantages.
Firstly, the clinker, sulfate source or SCM composition, cement
fineness, and other properties may well have changed in the 12
hours since the cement sample was collected, so the adjustment
indicated by the calorimetry test may no longer be the correct or
optimal one. In other words, the target or optimal Delta is assumed
to be constant for a clinker even through the chemistry of the
clinker, sulfate source, or SCM, or fineness of the cement has
changed, thus possibly resulting in a change of the optimal Delta.
Secondly, if the calorimetry indicates that Delta is far off from
the optimal value, then this means that sub-optimal cement has been
produced for the past 12 hours. In the case of optimizing and
adjusting based on strength measurements, this problem is even
worse, since, by definition, it requires at least 24 hours to
obtain a 1-day strength measurement.
Moreover, when considering management of more than one parameter
(in this case, strength and Delta), the inability for real-time
monitoring in current practice makes the control even more
difficult. For example, in order to adjust Delta, a calorimetry
test must be performed, which takes 8 hours at minimum. After the
result is received, an adjustment is made for example, to the
sulfate feed rate. After this has occurred, another sample must be
taken to determine the effect on strength. This test takes 24
hours. If an adjustment is made to strength, then the Delta must be
rechecked, which takes another 8 hours. Thus, a complete "cycle" of
adjustments takes 40 hours with the current technology. In 40
hours, for instance, 4000 MT of cement can be made, and as was
stated in the previous paragraph, it is possible that the
composition of the clinker, sulfate source or SCM has already
changed. Further, due to the long lead-time, larger changes must be
made, with increased risk that it is not in the right direction. A
real-time measure and manage system applied iteratively circumvents
these issues and allows the cement producer to produce a consistent
product.
A real-time solution is especially necessary if changes are made
outside of the mill, i.e. in the kiln. Based on the chemistry of
the clinker as determined by an NIR sensor on the cement produced,
or on the stream of clinker entering the mill, it may be desirable
to make changes to the raw material ratios into the kiln. This
would be much less advantageous if accomplished at intervals of 8
or more hours (i.e. as is possible with calorimetry today). Aside
from changes in the kiln raw meal, changes in the processing can
also be done based on clinker and finished sample monitoring.
During the classification of the cement within the classifier (236
of FIG. 9), coarse particles are recirculated back to the mill
(238) while finer particles are transferred to the cement silo
(250) as finished cement (244). In block 106 of FIG. 8, a LD signal
from the recirculated portion can be obtained. Based on this
signal, a fineness characteristic can be calculated, which, when
combined with a fineness characteristic of the finished cement, can
be used to determine how to change the particle size distribution
of the finished cement. Control of the classifier includes several
methods: air speed, volume loading, etc. Based on the combined LD
signals, one method may be more preferential than another.
Alternatively, an NIR sensor can replace or augment the LD sensor
to also provide a fineness characteristic.
It is also envisioned that an acoustic sensor that monitors the
grinding mill can provide information to the filling (of steel
balls) of the mill. This information may be useful for particle
size adjustments.
Another beneficial feature enabled by real-time monitoring and
management of the cement process is the ability to selectively make
certain properties constant. This is an advantage from a modeling
point of view, as predictions can become more accurate. For
example, in FIG. 15, Delta was held constant while strength was
predicted. Compared to FIG. 13, the cross-validation accuracy
improved 6 percentage points. Thus, it may be advantageous to first
adjust the Delta to the desired target and then adjust strength
(iteratively). Alternatively, the Blaine specific surface area can
be held constant (or at least the variation can be minimized
through a closed-loop control system, for example). In this case,
again, the improvement in the strength prediction can be
demonstrated.
In block 108 of FIG. 8, a temperature (T), moisture (M) or relative
humidity (RH) sensor (or a combination thereof) (234 or 254 of FIG.
9) can be used to give an indication of the gypsum dehydration.
This information can be used to correct for the dehydration by
adjusting the sulfate feed rate or other mill processes (e.g. water
spray) to adjust the ratio between gypsum and plaster. An NIR
sensor can also be used to determine the temperature, moisture or
relative humidity or even the dehydration rate directly. Similarly,
in block 108 of FIG. 8, the conduit (e.g. belt or air slide)
between the mill and the silo can be instrumented with T, M, RH
sensors or a combination thereof (234 of FIG. 9), or the cement
cooler between the mill and the silo to monitor the dehydration
during the transportation to the mill. And finally, the same type
of sensors can be instrumented in the silo itself (250) to provide
correction factors due to the dehydration, as shown in block 108 of
FIG. 8. Again, an NIR sensor can be used to collect similar
information.
Aside from gypsum dehydration, it is envisioned by the inventors
that pre-hydration can also be predicted from T, M, RH or NIR
sensors readings in these same locations.
The performance of cement additives depends on sulfate type and
content (gypsum, hemihydrate, anhydrite), on cement fineness and on
the degree of cement pre-hydration. Therefore, modifications on the
type and dosage of the cement additive need to consider the
advantages and disadvantages of changing other factors. The next
four examples illustrate some of these relationships.
Cement additives can affect Delta. A reduction in Delta may happen
when ingredients that chelate aluminum (such as alkanolamines or
sugars) are present in the cement additive. A higher sulfate
content can ensure Delta is within the preferred range for maximum
strength. Adapting to a Delta or to a compressive strength target
may therefore involve changing the composition of the cement
additive and/or adjusting the content of sulfate.
FIG. 16 shows the compressive strength at 1 day of EN-196-1:2016
mortars prepared with a cement ground in the laboratory using an
industrial ASTM C 150 type II/V clinker as a function of the active
dose of disodium ethanol diglycinate (Na.sub.2-EDG; dose in ppm of
cement) and the added content of SO.sub.3 (as gypsum and plaster).
3325 grams of crushed clinker were ground with 63.5 grams of gypsum
and 39.4 grams of plaster in a laboratory ball mill to a Blaine
specific surface area of 3,400 cm2/g to produce an initial cement
with 1.50% SO.sub.3. The SO.sub.3 weight ratio of this grind is
1:0.74 gypsum:plaster). The two other levels of SO.sub.3 (2.02% and
3.08%) were obtained by dry blending gypsum and plaster in the same
SO.sub.3 weight ratio as the initial cement prior to the mortar
mixing. The graph shows that there is 1.5-2.0 MPa strength decrease
of for every level of SO.sub.3 added and the performance trend of
Na.sub.2-EDG is independent of the changes in SO.sub.3 content in
the range tested.
In the next example, FIGS. 17, 18 and 19 show the compressive
strength at 1 day of EN-196 mortars prepared with cements ground in
the laboratory using industrial ASTM C 150 type I or I/II clinkers
as a function of both the active dose of different additives in ppm
of cement and SO.sub.3. The strength response is represented as a
contour plot. To produce these samples, 3325 grams of crushed
clinker were ground in a laboratory ball mill to a Blaine specific
surface area of either 3,300 or 4,300 cm2/g without any source of
calcium sulfate. The levels of SO.sub.3 tested for each clinker
were obtained by dry blending gypsum and plaster to the ground
cement prior to the mortar mixing.
FIGS. 17 and 18 compare two different additives (diethanol
isopropanolamine (DEIPA), and triethanol amine (TEA)) within the
same cement. The contour plots in FIGS. 17 and 18 demonstrate the
complexity of the additive efficiency, as it depends on both the
additive dosage and the sulfate content for Cement 2. The present
invention can ensure that the proper ranges of both are satisfied
to maximize efficiency of the additive. In FIG. 19, DEIPA is added
to a different cement (Cement 3). In comparing FIGS. 17 and 19, it
is demonstrated that the response is different depending on the
cement. Thus, in order to optimize additives for properties such as
strength, real-time sulfate and strength predictions based on for
example, and NIR signal, can help to determine optimal additive
dosages. For example, adjustments can be made to move the system in
a certain sulfate range.
The principles, preferred embodiments, and modes of operation of
the present invention have been described in the foregoing
specification. The invention which is intended to be protected
herein, however, is not to be construed as limited to the
particular forms disclosed, since these are to be regarded as
illustrative rather than restrictive. Skilled artisans can make
variations and changes without departing from the spirit of the
invention.
* * * * *
References